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All active MLOps roles based in United States.
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AI Infrastructure Engineer
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Here at Scout Motors, we're carrying forward the heritage of one of the most iconic American vehicles in history. A vehicle dating back to 1960. One that forged the path for future generations of rugged SUVs and trucks and will do so once again.
But Scout is more than just a brand, it’s a legacy steeped in a culture of exploration, caretaking, and hard work.
The Scout brand is all about respect. Respect for the past and the future by taking an iconic American brand that hasn’t been around for a while, electrifying it, digitizing it, and loading it with American innovation. Respect for communities by creating a company that stands for its people and its customers. Respect for both work and play, with vehicles that are equally at home at a camp site, a job site, or on a Tuesday commute. And respect for our customers by developing two powertrains that meet their requirements — an all-electric powertrain as well as the Harvester™ range extender powertrain which includes a built-in gas-powered generator with an estimated 500 miles of combined range.
At Scout Motors, we empower our talented, inclusive, and entrepreneurial teams to innovate. What makes a Scout employee? Someone who is a visionary and a leader, who seeks new paths and shares lessons learned. A knowledgeable doer who collaborates across the company to build better. A go-getter with unrivaled passion.
Join us at Scout Motors and be part of shaping the future of transportation. If you're ready to drive change and make history, apply now!
What you’ll do
Become part of an iconic brand that is set to revolutionize the electric pick-up truck & rugged SUV marketplace by achieving the following:
- Install, configure, and maintain AI platform and tools.
- Design, deploy, and operate infrastructure supporting ML and LLM workloads.
- Build, containerize, and deploy AI services using Docker.
- Build and maintain Machine Learning CI/CD pipelines for training, testing, and deployment.
- Deploy and manage AI services across cloud and on-prem environments.
- Automate infrastructure provisioning using Terraform and Infrastructure-as-Code best practices.
- Monitor system performance, reliability, and scalability of AI platforms.
- Implement observability for agentic AI systems to ensure reliability, transparency, and debuggability.
- Perform regular security updates, patching, access control, and vulnerability remediation.
- Integrate AI tools with APIs, data platforms, and internal systems.
- Research, evaluate, and prototype new AI, LLM, and MLOps tools.
- Troubleshoot infrastructure, data, and deployment issues.
- Research, test, and prototype emerging AI technologies.
- Document system architecture, deployment processes, and operational runbooks.
Location & Travel Expectations:
- This role is based out of the Scout Motors corporate headquarters in Charlotte, NC.
- This role requires 4-5 days per week in the office, with regular in-person meetings and events.
- Applicants should expect that the role will require the ability to convene with Scout colleagues in person and travel to participate in events on behalf of the company from time to time.
What you’ll bring
We expect all Scout employees to have integrity, curiosity, resourcefulness, and strive to exhibit a positive attitude, as well as a growth mindset. You’ll be comfortable with change and flexible in a fast-paced, high-growth environment. You’ll take a collaborative approach to achieve ambitious goals. Here's what else you'll bring:
- Bachelor's degree in computer science, information technology, or related field or equivalent work experience.
- 7+ years Practical experience with LLM platforms, LLMOps, and MLOps.
- Experience deploying and maintaining AI or data platforms in production.
- Hands-on experience with AI/automation tools.
- Experience designing and orchestrating agentic automation workflows.
- Strong experience with Terraform and Infrastructure-as-Code.
- Proven experience deploying applications using Docker (Docker files, image optimization, container lifecycle).
- Expertise with cloud platforms such as AWS.
- Expertise with CI/CD tooling (GitHub Actions, GitLab CI).
- Strong Knowledge of Kubernetes and orchestration.
- Solid understanding of networking.
- Experience supporting high-availability, production AI systems.
- Scripting skills (Python, PySpark, Bash).
- Knowledge of security best practices, patch management, and access controls.
- Collaborate with engineering, data, and product teams to support AI initiatives.
- Excellent problem-solving and troubleshooting skills. When a problem occurs, you run towards it not away.
- Effective communication and collaboration skills. You treat colleagues with respect. You have a desire for clean implementations but are also humble in discussing alternative solutions and options.
- A teaching and coaching approach to guiding engineers and teams in approaches.
- Minimum of High School Diploma, GED or equivalent required for all roles at Scout Motors, Inc.
What you'll gain
The benefits of joining Scout include the chance to build products and a company from the ground up. This is a chance to create something new and lasting – with an iconic brand at its foundation. In addition, Scout provides competitive compensation and benefits to support your physical, mental, and financial wellbeing. Program specifics are detailed in company policies and employee benefit guides, select highlights:
- Competitive insurance including:
- Medical, dental, vision and income protection plans
- 401(k) program with:
- An employer match and immediate vesting
- Generous Paid Time Off including:
- 20 days planned PTO, as accrued
- 40 hours of unplanned PTO and 14 company or floating holidays, annually
- Up to 16 weeks of paid parental leave for biological and adoptive parents of all genders
- Paid leave for circumstances related to bereavement, jury duty, voting time, or military leave
Pay Transparency
This is a full-time, exempt position eligible to receive a base salary and to participate in an annual performance bonus program. Final salary offered will be determined based on factors including but not limited to the candidate's skills and experience. The annual performance bonus program is preset and not candidate dependent.
Initial base salary range = $140,000.00 - $170,000.00
Internal leveling code: IC8
Notice to applicants:
- To be considered for career opportunities at Scout Motors, applicants must be 18 years of age or older.
- Residing in San Francisco: Pursuant to the San Francisco Fair Chance Ordinance, Scout Motors will consider for employment qualified applicants with arrest and conviction records.
- Residing in Los Angeles: Scout Motors will consider for employment qualified applicants with criminal histories in a manner consistent with the Los Angeles Fair Chance Initiative for Hiring Ordinance.
- Residing in New York City: This role is not eligible for remote work in New York City.
Equal Opportunity
Scout Motors is committed to employing a diverse workforce and is proud to be an Equal Opportunity Employer. Qualified applicants will receive consideration without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity, gender expression, veteran status, disability, pregnancy, or any other characteristics protected by law. Scout Motors is committed to compliance with all applicable fair employment practice laws. If you require reasonable accommodation to complete a job application, pre-employment testing, or a job interview or to otherwise participate in the hiring process, please contact ScoutAccommodations@scoutmotors.com.
Ready to apply?
Apply to Scout Motors
Archer is an aerospace company based in San Jose, California building an all-electric vertical takeoff and landing aircraft with a mission to advance the benefits of sustainable air mobility. We are designing, manufacturing, and operating an all-electric aircraft that can carry four passengers while producing minimal noise.
Our sights are set high and our problems are hard, and we believe that diversity in the workplace is what makes us smarter, drives better insights, and will ultimately lift us all to success. We are dedicated to cultivating an equitable and inclusive environment that embraces our differences, and supports and celebrates all of our team members.
As a Senior DevOps Engineer, you will be a key contributor to our infrastructure strategy, focusing on automation, stability, and performance across both cloud and on-premise environments. You will drive best practices in CI/CD, configuration management, and monitoring, with a specific focus on optimizing the deployment and operation of large language models (LLMs) and related technologies.
Responsibilities
- Design, deploy, and manage highly available, scalable infrastructure using Kubernetes and Docker across public cloud (e.g., AWS, GCP, Azure) and on-premise data centers.
- Develop and maintain robust Configuration Management solutions (e.g., Ansible, Terraform) for consistent environment provisioning and management.
- Implement and manage CI/CD pipelines to facilitate rapid, reliable, and automated software releases.
- Administer and troubleshoot operating systems, encompassing both Linux and Windows environments.
- Implement and optimize observability practices using monitoring tools like Datadog for logging, tracing, and alerting.
- Spearhead the operational deployment, scaling, and maintenance of LLM infrastructure, leveraging tools like LiteLLM, OpenRouter, or similar LLM orchestration/gateway technologies.
- Automate repetitive tasks and system operations using scripting languages, primarily Bash and Python.
- Collaborate closely with development, MLOps, and security teams to ensure infrastructure supports product requirements and compliance standards.
- Participate in an on-call rotation to ensure service reliability and responsiveness to incidents.
Qualifications
Required Skills
- 5+ years of professional experience in a DevOps, SRE, or infrastructure engineering role.
- Deep expertise in containerization and orchestration, specifically Kubernetes (design, deployment, and troubleshooting) and Docker.
- Strong proficiency in managing infrastructure in both Cloud (e.g., AWS, GCP, Azure) and On-Premise environments.
- Expert-level administration skills in Linux and strong working knowledge of Windows Server environments.
- Proven experience with Infrastructure as Code (IaC) and Configuration Management tools (e.g., Terraform, Ansible).
- High proficiency in scripting and automation using Python and Bash.
- Extensive experience with monitoring and observability platforms, especially Datadog (or comparable tools like Prometheus/Grafana, New Relic).
- Hands-on experience deploying and managing technologies related to Large Language Models (LLMs), such as utilizing LiteLLM, OpenRouter, or setting up and managing LLM serving endpoints.
Nice-to-Have Skills
- Experience with specific Kubernetes distributions (e.g., K3s, Rancher, OpenShift).
- Familiarity with network configuration, firewalls, and security best practices for hybrid environments.
- Experience in MLOps workflows and related tools (e.g., MLflow, Kubeflow).
- Certifications such as CKA, CKAD, or relevant cloud provider certifications.
Please note that this job description is intended to provide a general overview of the position and does not include an exhaustive list of responsibilities and qualifications
At Archer we aim to attract, retain, and motivate talent that possess the skills and leadership necessary to grow our business. We drive a pay-for-performance culture and reward performance that supports the Company’s business strategy. For this position we are targeting a base pay between $133,400 - $200,000. Actual compensation offered will be determined by factors such as job-related knowledge, skills, and experience.
Archer is proud to be an Equal Opportunity employer committed to diversity and inclusivity in the workplace. All aspects of employment are decided on the basis of merit, qualifications, and business needs. We do not discriminate based upon race, color, religion, sex, sexual orientation, age, national origin, disability status, protected veteran status, gender identity or any other characteristic protected by federal, state or local laws. Successful candidates must be able to demonstrate U.S. citizenship, permanent residency, or status as a protected individual to satisfy ITAR, contractual, and/or regulatory requirements.
Archer is committed to working with and providing reasonable accommodations to job applicants with physical or mental disabilities, and those with sincerely held religious beliefs. Applicants who may require reasonable accommodation for any part of the application or hiring process should provide their name and contact information to Archer’s People Team at people@archer.com. Reasonable accommodations will be determined on a case-by-case basis.
Archer is committed to working with and providing reasonable accommodations to job applicants with physical or mental disabilities, and those with sincerely held religious beliefs. Applicants who may require reasonable accommodation for any part of the application or hiring process should provide their name and contact information to Archer’s People Team at people@archer.com. Reasonable accommodations will be determined on a case-by-case basis.
Information collected and processed as part of any job applications you choose to submit is subject to Archer's Candidate Privacy Policy.
Archer is unable to provide work visa sponsorship for this position at the present time.
Archer is proud to be an Equal Opportunity employer committed to diversity and inclusivity in the workplace. All aspects of employment are decided on the basis of merit, qualifications, and business needs. We do not discriminate based upon race, color, religion, sex, sexual orientation, age, national origin, disability status, protected veteran status, gender identity or any other characteristic protected by federal, state or local laws.
Archer Aviation does not engage with external recruiting agencies/individual recruiters with whom it does not have a prior written agreement. Archer reserves the right to make use of any unsolicited resumes that it receives and bears no responsibility for payment of any fees asserted from the use of unsolicited resumes. If you are a recruiting agency or individual recruiter wishing to do business with Archer, please reach out to People@archer.com. All employment processes are managed by the Archer People Team.
Ready to apply?
Apply to Archer
Sr. Director, Data Platform Engineering & Operations
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Why Sony Interactive Entertainment?
Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity.
Sr. Director Data Platform Engineering & Operations
San Diego, CA
The Sr. Director Data Platform Engineering & Operations is a critical leadership role at SIE, responsible for driving innovation and scalability across the company’s data and AI platform ecosystem. This role oversees platforms including Data Infrastructure (Streaming, Ingestion, Warehouse, and Data Ocean), Experimentation and Audience Platforms, and Governance & Data Observability tools.
In this role, you will ensure SIE’s platforms process massive volumes of data, delivering insights that enhance Player, Creator, Publisher, and Enterprise experiences. By enabling data-driven decisions at scale, you will drive the future of personalized gaming, efficient operations, and enterprise productivity through advanced AI and machine learning technologies.
As a strategic leader, you will define and execute the vision for SIE’s data and AI platform ecosystem, ensuring scalable solutions that support key business objectives across gaming, content creation, and enterprise operations. Reporting to the VP of Data & AI, you will lead global teams of engineers and experts to build platforms that democratize data and transform decision-making across the company. Priority consideration will be given to candidates with proven experience in a previous or current Sr. Director level role.
This highly cross-functional role works closely with senior leadership in engineering, product, and business to align the platform ecosystem with the organization’s strategic goals.
Key Responsibilities:
Strategic Leadership:
- Define the long-term vision for SIE’s Data and AI Platform ecosystem, aligning with business goals and driving value across Player, Creator, Publisher, and Enterprise touchpoints.
- Lead the development of platforms that process large-scale, real-time data from millions of users, delivering insights to enhance gaming experiences, content creation, and enterprise productivity.
- Build scalable platforms for personalized player experiences, content creation tools, and enterprise efficiency, optimizing performance and cost-effectiveness.
Platform Development & Operations:
- Provide thought leadership in the design, architecture, and execution of the platform ecosystem, ensuring innovation and seamless integration with SIE’s global gaming services and enterprise operations.
- Ensure platforms are optimized for performance, scalability, and reliability, processing billions of data points daily across Player, Creator, Publisher, and Enterprise activities.
- Champion operational excellence by driving continuous improvements in platform cost efficiency, performance, and security to support SIE’s global user base.
Cross-functional Collaboration:
- Collaborate with senior leaders to deliver data and AI solutions that drive value across gaming, content creation, and enterprise operations.
- Work with teams to ensure data platforms improve engagement, content creation, monetization, and efficiency.
- Ensure compliance with privacy, security, and regulatory requirements while supporting scalable data operations.
Innovation & Efficiency:
- Lead efforts to optimize platform performance, reduce costs, and improve data accessibility across gaming and enterprise operations.
- Implement innovative solutions to scale data operations and maximize value from Player, Creator, Publisher, and Enterprise data.
- Drive AI/ML adoption to enhance gaming experiences, content discovery, operational efficiency, and enterprise workflows.
Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.
Experience:
Technical Expertise:
- 15+ years of experience in data engineering, platform engineering, or related fields, with deep expertise in designing and building distributed data systems and large-scale data warehouses.
- Proven track record of architecting platforms capable of processing petabytes of data and supporting the real-time ingestion and processing of billions of data points daily across gaming and enterprise domains.
- Extensive experience in building and scaling cloud-native architectures (AWS, Azure, GCP) for data platforms, with a strong focus on high availability, fault tolerance, and cost-efficiency.
- Demonstrated success in growing and evolving data platforms to meet the needs of a rapidly scaling business, ensuring data-driven decisions are made at all levels of the organization.
- Extensive experience with Kafka for data streaming and real-time data ingestion.
- Strong hands-on knowledge of Databricks and Snowflake for scalable data engineering, analytics, and cloud data warehousing.
- Proven experience making buy vs. build decisions, assessing in-house development versus integrating third-party platforms based on cost, scalability, and business needs.
- Expertise with Data Governance tools such as Alation and Collibra for managing data catalogs, compliance, and data quality.
- Knowledge and experience with Data Observability tools to monitor data pipelines and ensure data accuracy, reliability, and transparency.
- Experience with experimentation platforms such as Optimizely, Statsig, and LaunchDarkly, with a focus on A/B testing and feature management.
- Expertise in AI/ML platforms like AWS SageMaker and Databricks MLflow for machine learning model development, deployment, and MLOps practices.
Leadership & Strategic Skills:
- Proven leadership (in a prior Sr. Director level role strongly preferred) building and leading high-performing global engineering teams, balancing short-term execution with long-term strategic growth.
- Strong strategic mindset, translating business objectives into scalable technical solutions that deliver value across the organization.
- Excellent communication and collaboration skills, driving impactful solutions across engineering, product, and business teams.
#LI-GD1
Please refer to our Candidate Privacy Notice for more information about how we process your personal information, and your data protection rights.
At SIE, we consider several factors when setting each role’s base pay range, including the competitive benchmarking data for the market and geographic location.
Please note that the base pay range may vary in line with our hybrid working policy and individual base pay will be determined based on job-related factors which may include knowledge, skills, experience, and location.
In addition, this role is eligible for SIE’s top-tier benefits package that includes medical, dental, vision, matching 401(k), paid time off, wellness program and coveted employee discounts for Sony products. This role also may be eligible for a bonus package. Click here to learn more.
Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks.
Please refer to our Candidate Privacy Notice for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights.
Equal Opportunity Statement:
Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category.
We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond.
Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.
Ready to apply?
Apply to PlayStation Global
Sr. Director, Data Platform Engineering & Operations
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Why Sony Interactive Entertainment?
Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity.
Sr. Director Data Platform Engineering & Operations
San Mateo, CA
The Sr. Director Data Platform Engineering & Operations is a critical leadership role at SIE, responsible for driving innovation and scalability across the company’s data and AI platform ecosystem. This role oversees platforms including Data Infrastructure (Streaming, Ingestion, Warehouse, and Data Ocean), Experimentation and Audience Platforms, and Governance & Data Observability tools.
In this role, you will ensure SIE’s platforms process massive volumes of data, delivering insights that enhance Player, Creator, Publisher, and Enterprise experiences. By enabling data-driven decisions at scale, you will drive the future of personalized gaming, efficient operations, and enterprise productivity through advanced AI and machine learning technologies.
As a strategic leader, you will define and execute the vision for SIE’s data and AI platform ecosystem, ensuring scalable solutions that support key business objectives across gaming, content creation, and enterprise operations. Reporting to the VP of Data & AI, you will lead global teams of engineers and experts to build platforms that democratize data and transform decision-making across the company. Priority consideration will be given to candidates with proven experience in a previous or current Sr. Director level role.
This highly cross-functional role works closely with senior leadership in engineering, product, and business to align the platform ecosystem with the organization’s strategic goals.
Key Responsibilities:
Strategic Leadership:
- Define the long-term vision for SIE’s Data and AI Platform ecosystem, aligning with business goals and driving value across Player, Creator, Publisher, and Enterprise touchpoints.
- Lead the development of platforms that process large-scale, real-time data from millions of users, delivering insights to enhance gaming experiences, content creation, and enterprise productivity.
- Build scalable platforms for personalized player experiences, content creation tools, and enterprise efficiency, optimizing performance and cost-effectiveness.
Platform Development & Operations:
- Provide thought leadership in the design, architecture, and execution of the platform ecosystem, ensuring innovation and seamless integration with SIE’s global gaming services and enterprise operations.
- Ensure platforms are optimized for performance, scalability, and reliability, processing billions of data points daily across Player, Creator, Publisher, and Enterprise activities.
- Champion operational excellence by driving continuous improvements in platform cost efficiency, performance, and security to support SIE’s global user base.
Cross-functional Collaboration:
- Collaborate with senior leaders to deliver data and AI solutions that drive value across gaming, content creation, and enterprise operations.
- Work with teams to ensure data platforms improve engagement, content creation, monetization, and efficiency.
- Ensure compliance with privacy, security, and regulatory requirements while supporting scalable data operations.
Innovation & Efficiency:
- Lead efforts to optimize platform performance, reduce costs, and improve data accessibility across gaming and enterprise operations.
- Implement innovative solutions to scale data operations and maximize value from Player, Creator, Publisher, and Enterprise data.
- Drive AI/ML adoption to enhance gaming experiences, content discovery, operational efficiency, and enterprise workflows.
Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.
Experience:
Technical Expertise:
- 15+ years of experience in data engineering, platform engineering, or related fields, with deep expertise in designing and building distributed data systems and large-scale data warehouses.
- Proven track record of architecting platforms capable of processing petabytes of data and supporting the real-time ingestion and processing of billions of data points daily across gaming and enterprise domains.
- Extensive experience in building and scaling cloud-native architectures (AWS, Azure, GCP) for data platforms, with a strong focus on high availability, fault tolerance, and cost-efficiency.
- Demonstrated success in growing and evolving data platforms to meet the needs of a rapidly scaling business, ensuring data-driven decisions are made at all levels of the organization.
- Extensive experience with Kafka for data streaming and real-time data ingestion.
- Strong hands-on knowledge of Databricks and Snowflake for scalable data engineering, analytics, and cloud data warehousing.
- Proven experience making buy vs. build decisions, assessing in-house development versus integrating third-party platforms based on cost, scalability, and business needs.
- Expertise with Data Governance tools such as Alation and Collibra for managing data catalogs, compliance, and data quality.
- Knowledge and experience with Data Observability tools to monitor data pipelines and ensure data accuracy, reliability, and transparency.
- Experience with experimentation platforms such as Optimizely, Statsig, and LaunchDarkly, with a focus on A/B testing and feature management.
- Expertise in AI/ML platforms like AWS SageMaker and Databricks MLflow for machine learning model development, deployment, and MLOps practices.
Leadership & Strategic Skills:
- Proven leadership in building and leading high-performing global engineering teams, balancing short-term execution with long-term strategic growth.
- Strong strategic mindset, translating business objectives into scalable technical solutions that deliver value across the organization.
- Excellent communication and collaboration skills, driving impactful solutions across engineering, product, and business teams.
#LI-GD1
Please refer to our Candidate Privacy Notice for more information about how we process your personal information, and your data protection rights.
At SIE, we consider several factors when setting each role’s base pay range, including the competitive benchmarking data for the market and geographic location.
Please note that the base pay range may vary in line with our hybrid working policy and individual base pay will be determined based on job-related factors which may include knowledge, skills, experience, and location.
In addition, this role is eligible for SIE’s top-tier benefits package that includes medical, dental, vision, matching 401(k), paid time off, wellness program and coveted employee discounts for Sony products. This role also may be eligible for a bonus package. Click here to learn more.
Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks.
Please refer to our Candidate Privacy Notice for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights.
Equal Opportunity Statement:
Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category.
We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond.
Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.
Ready to apply?
Apply to PlayStation Global
Lead Product Manager, Data Science
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Who We Are
2K is headquartered in Novato, California and is a wholly owned label of Take-Two Interactive Software, Inc. (NASDAQ: TTWO). Founded in 2005, 2K Games is a global video game company, publishing titles developed by some of the most influential game development studios in the world. Our studios responsible for developing 2K’s portfolio of world-class games across multiple platforms, include Visual Concepts, Firaxis, Hangar 13, CatDaddy, Cloud Chamber, 31st Union, HB Studios, and 2K SportsLab. Our portfolio of titles is expanding due to our global strategic plan, building and acquiring exciting studios whose content continues to inspire all of us! 2K publishes titles in today’s most popular gaming genres, including sports, shooters, action, role-playing, strategy, casual, and family entertainment.
Our team of engineers, marketers, artists, writers, data scientists, producers, thinkers and doers, are the professional publishing stewards of 2K’s portfolio currently includes several AAA, sports and entertainment brands, including global powerhouse NBA®️ 2K, renowned BioShock®️, Borderlands®️, Mafia, Sid Meier’s Civilization®️ and XCOM®️ brands; popular WWE®️ 2K and WWE®️ SuperCard franchises, TopSpin 2K25, as well as the critically and commercially acclaimed PGA TOUR®️ 2K.
At 2K, we pride ourselves on creating an inclusive work environment, which means encouraging our teams to Come as You Are and do your best work! We encourage ALL applicants to explore our global positions, even if they don’t meet every requirement for the role. If you're interested in the job and think you have what it takes to work at 2K, we encourage you to apply!
What You Will Do
2K Games is building a world-class data ecosystem to power real-time analytics, machine learning, and game intelligence across all our franchises. We are looking for a Senior Product Manager, Data Science to drive the vision, strategy, and execution of our data science strategies and products, partnering with game studios and analytics teams to enable enhanced player experiences.
This role requires a blend of strategic development, product management expertise, and technical understanding of data science and machine learning (ML) methodologies. The ideal candidate will seamlessly integrate data-driven strategies with player-centric goals, ensuring AI and analytics improve game design, live operations, and business intelligence.
Strategic Vision & Product Leadership
- Develop and implement the product strategy for 2K’s central data science platform, partnering with Data Scientists across our gaming business units to drive predictive analytics, player personalization, and real-time decision-making;
- Collaborate with the Director of Product, 2K Data to align the data engineering roadmap with customer objectives and player-centric outcomes;
- Define and prioritize a high-impact data science roadmap to lead a team of central data scientists in driving a variety of use cases such as player retention modeling, dynamic content generation, and real-time fraud detection.
Data Science Platform Development
- Lead the development of reusable and extensible machine learning models, feature engineering pipelines, and ML-driven insights using tools like Databricks, MLflow, and SageMaker;
- Ensure data science initiatives integrate seamlessly with the real-time data infrastructure, supporting streaming analytics, AI-powered LiveOps, and dynamic matchmaking systems;
- Establish and maintain self-service tools that enable game teams to experiment with and deploy AI models independently;
- Support the build and enhancement of the central ML feature store;
- Monitor and optimize model performance in production environments, using MLOps standard methodologies;
- Implement governance frameworks to ensure AI models adhere responsibly to data privacy, security, and compliance standards (e.g., CCPA, GDPR).
Cross-Functional Collaboration
- Work closely with data scientists across game studios and business units to understand their data science needs and to provide data-driven solutions at the pace they need them;
- Act as a strategic liaison between data scientists and product teams, ensuring model outputs are actionable, reliable, and aligned with business goals;
- Promote a culture of experimentation and rapid iteration, supporting game studios with A/B testing frameworks, predictive analytics, and personalization engines.
- Find opportunities to enhance game design and player engagement through advanced analytics and machine learning.
What You Need
- 7+ years of experience in product management with a focus on data science, analytics, or ML-driven products
- 5+ years of experience in gaming, technology, or entertainment industries;
- Strong understanding of data science methodologies, such as predictive modeling, natural language processing, and computer vision;
- Experience with data science tools and platforms, such as Python, SQL, Databricks,TensorFlow, and R;
- Customer-focused mentality with focus on the Why and What without getting lost in the What and the How;
- Consistent track record of delivering data science products and features from ideation to production, with measurable business impact;
- Ability to translate complex data insights into clear product strategies and business opportunities;
- Knowledge of real-time analytics platforms, streaming data processing, and feature store management;
- Familiarity with data governance frameworks, model risk management, and MLOps standard processes preferred;
- Advanced degree or equivalent experience in Data Science, Machine Learning, Computer Science, or a related field preferred.
The pay range for this position in California at the start of employment is expected to be between $109,800 and $162,480 per Year. However, base pay offered is based on market location, and may vary further depending on individualized factors for job candidates, such as job-related knowledge, skills, experience, and other objective business considerations. Subject to those same considerations, the total compensation package for this position may also include other elements, including a bonus and/or equity awards and eligibility to participate in our 401(K) plan and Employee Stock Purchase Program. Regular, full-time employees are also eligible for a range of benefits at the Company, including: medical, dental, vision, and basic life insurance coverage; 14 paid holidays per calendar year; paid vacation time per calendar year (ranging from 15 to 25 days) or eligibility to participate in the Company’s discretionary time off program; up to 10 paid sick days per calendar year; paid parental and compassionate leave; wellbeing programs for mental health and other wellness support; family planning support through Maven; commuter benefits; and reimbursements for fitness-related expenses.
As an equal opportunity employer, we are committed to ensuring that qualified individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform their essential job functions, and to receive other benefits and privileges of employment. Please contact us if you need reasonable accommodation.
Please note that 2K Games and its studios never uses instant messaging apps or personal email accounts to contact prospective employees or conduct interviews and when emailing, only use 2K.com accounts.
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Go-To-Market (GTM) Digital Natives Program Leader
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SLSQ127R420
While candidates in the listed location(s) are encouraged for this role, candidates in other locations will be considered.
As the GTM Digital Native Programs Leader, you will operate as the de facto COO and scale pipeline and consumption for th high growth Databricks’ Digital Native vertical. You will partner in a "two-in-a-box" model with the Industry GTM Leader to translate strategy into durable, repeatable commercial execution across a rapidly scaling global field organization. You will work closely with sales and field engineering leaders to ideate, build, execute and scale global programs.
You will play a critical role in shaping Databricks’ growth trajectory. You will be part of a lean GTM leadership that powers sellers to deliver measurable business outcomes through scale & leverage. You will be the lead orchestrator for your industry vertical, at the center of a mandate to inspire executives, drive industry outcomes, and unleash Databricks’ partner ecosystem in the high-growth SaaS space.
The Impact You Will Have
Strategy & Operating Model
- Operating Model Ownership: Own and implement end-to-end op-model (across Sales, FE, Product, Engineering, Developer Relations, Partners) in a consistent global approach.
- Product-GTM Strategy: Inform the annual Digital Native strategy by synthesizing product telemetry and engineering roadmaps with field signals to identify Big Bets in the digital natives space.
- Data-Driven Product Feedback: Synthesize learnings from internal (field, product, engineering, developer relations) & external (customer, partner, developers) stakeholders into durable best practices
Market Presence & Influence
- Internal Executive Influence: Wield two-way influence on Databricks’ Field (Sales, FE, Business Dev), Product & Engineering leadership: i.e., reflect industry signals in product roadmaps, as well as translate product activation goals into verticalized industry programs
- Market Presence: Own and engage with technical & business customer and partner executives, build market presence to uncover signals on technical friction, business value and Databricks differentiators.
- Industry Evangelism: Serve as a visible evangelist & thought leader (e.g., open source advocacy, scaling AI adoption), representing Databricks’ at key customer, partner, industry and developer forums
Execution & Accountability
- Full-Funnel Program Design: Select & design the industry’s programs across products (and verticalize product programs) across the full funnel: demand generation → pipe creation & progression → consumption
- Asset Creation: Create high-quality and scalable program assets that will be used by the full field (Sales, FE, BD, Marketing, Ecosystem) at scale
- Field Activation & Community: Drive continuous field adoption of program assets and outcomes by cross-pollinating best practices across product and field teams in high-impact community cadences.
- Ecosystem Integration: Collaborate with the partnership, ISV, and Data Marketplace teams to drive adoption of a seamless, interconnected data-sharing ecosystem.
- Outcome Measurement: Deliver commercial outcomes by establishing measurement and monitoring systems that track product telemetry, industry & partner program performance.
- Executive Accountability: Drive cross-functional leadership accountability for program adoption and outcomes through continuous monitoring and executive influence.
What We Look For
Strategic & Operational Mindset
- COO Mindset: Proven ability to act as the operational backbone of a business vertical, focusing on pipeline health, organizational efficiency, and execution.
- Strategic Execution: A track record of defining and translating complex industry strategies into durable, "field-ready" commercial motions for large organizations.
- Programmatic Vision: Experience developing global, scalable GTM frameworks - moving beyond "one-off" deals to create a scalable engine for growth.
Technical & Domain Expertise
- Technical Chops: Technical knowledge on Databricks critical for this market. Comfort with discussing AI & LLM, Lakehouse, Lakebase, governance
- Industry POV: A strong point of view on macro trends in high-growth SaaS and key persona triggers, helping to shape our industry advantage against peers.
- Open Source Knowledge: A strong understanding of the open-source ecosystem and how it integrates with proprietary enterprise platforms.
- AI Builder Experience: Proven track record of hands-on experience building AI systems (MLOps, GenAI apps, or large-scale predictive models).
Execution & Analytical Skills
- Full-Funnel Expertise: Deep understanding of sales play mechanics, including lead generation, pipeline progression, and consumption drivers.
- Scale Orientation: A "multiplier" mindset with a passion for activating large-scale field organizations and cross-pollinating best practices.
- Entrepreneurial Spirit: A "doer" mindset with the ability to operate in a fast-paced, ambiguous environment and drive results across cross-functional teams.
Leadership & Scale
- Influence Without Hierarchy: Ability to influence & drive outcomes across senior executives & global teams via influence, clarity & presence versus direct reporting lines.
- Cross-Functional Orchestration: Skill in collaborating with Product, Engineering, and BD leadership to align product roadmap shifts with commercial requirements specific to high-growth SaaS customers.
Pay Range Transparency
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected base salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipated utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.
About Databricks
Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
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Software Engineer - Product
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About The Role
This is a product-focused full-stack engineering role on a team building AI-driven power-user applications in the CAD/CAM space. You'll work across the entire stack—from crafting intuitive user experiences to building robust backend services—with a direct line of sight to how your work impacts real users.
But this isn't your typical full-stack role. Our team regularly dives into technically deep work: platform engineering, MLOps, systems-level challenges, and performance-critical code. We're looking for engineers who aren't afraid to roll up their sleeves and tackle complex problems outside the usual web development comfort zone.
The ideal candidate is a highly motivated self-starter who is passionate about software engineering, cares deeply about the user experience, and thrives when facing technically demanding problems.
About The Team
We're a team of nerds who genuinely love what we do. We're passionate about building great products and obsess over the details that make software feel right.
We're also the kind of people who get excited about stepping outside our comfort zones. Whether it's picking up a new technology, diving into an unfamiliar domain, or tackling a gnarly technical challenge, we see those moments as opportunities to grow. If you're the type who lights up when facing a hard problem rather than shying away from it, you'll fit right in.
At ReCAM, we are building new, automation-first, computer-aided manufacturing (CAM) applications. It’s early stage, which means we ship fast and adapt as we learn from user testing. At the same time, we strive for the kind of technical excellence that enables rapid development. If you enjoy building new and cool software, you’ll love it here!
Export Control Requirement: Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.
Our Ideal Candidate
- You’re chasing full-stack mastery– you’ve encountered multiple frameworks and have the scars to prove it
- You are independent, eager to learn and take ownership, enthusiastic about technology and development
- You know your stuff, but are not scared to admit knowledge gaps and accept constructive criticism
- You believe in consensus-based decision making and engaging in technical reasoning as a way to establish team-wide software engineering standards
- You can engage in thoughtful peer review of others' work
Your First 6 Months
- Week 1-2: Ship your first contribution to the product.
- Months 2–3: Take ownership of major product areas and drive features end-to-end.
- Month 6: Become a subject matter expert in some aspect of our work—the person the team turns to for guidance in that area.
Compensation Range: Annual salary for this position is expected to be between $93,000 to $140,000 plus participation in our annual bonus plan and long term incentive plan. The actual pay may be higher depending on your qualifications and experience.
Required Qualifications
- Bachelors in CS and 2 years in industry, or equivalent work experience
- Solid understanding of TypeScript and familiarity with at least one modern frontend framework such as React, Vue, Svelte, Angular
- Proficiency in writing backend APIs in strongly typed languages such as TypeScript, C#, Java, Go, or equivalent
- Strong CS fundamentals - understanding of networking and web technologies like REST APIs, gRPC, web-sockets, databases, HTML, CSS, etc. as well as a grasp on common OOP, functional programming and software architecture concepts
- Deep experience with at least one relational or non-relational database
- Familiarity with AWS or equivalent providers like Azure or GCP
- Understand proper usage of git and docker/containers
Nice-To-Have's
- Bonus points for python3 chops, prior experience with data-engineering or Machine Learning Operations
- Bonus points for prior experience with tanstack query, router, start, etc.
- Some experience with C++ / cmake, CUDA, CAD, CAM, graphics APIs
- Prior start-up, early-stage or greenfield experience
- Personal projects/portfolio you would love to share and talk about
Interview Process
- Recruiter connection
- Hiring manager screen
- Take home assessment
- Interview panel (4 rounds):
- 20–30 min: Product demo and alignment with product team
- 45 min: Live coding assessment, focused on practical work
- 15 min: Break
- 60 min: System design panel
- 45 min: Technical Q&A panel
You'll get a chance to meet the whole team you'd be working with daily.
About Re:Build Manufacturing
Re:Build Manufacturing is a growing family of industrial and engineering businesses combining enabling technologies, operational superiority, and strategic M&A to build America’s next generation industrial company. At Re:Build we deploy deep expertise in engineering, operations management, and technology to supercharge the performance of our member companies. We demonstrate deep professional expertise and a candid, principled operating culture to drive differentiated outcomes. Ours is a fast-paced environment where individuals can stretch and be challenged to pursue their fullest potential.
Re:Build was founded to pioneer a profitable model for the revitalization of US manufacturing. We’ve assembled a powerful set of complimentary capabilities and lines of business that enable us to pursue a wide range of end markets. Our acquired businesses are grounded in build-to-print and by-the-hour engineering and design services, and we’re employing their combined expertise to migrate to increasingly sophisticated program development and production, as well as the generation of our own products. Our unique set of capabilities lend themselves to highly complex systems and products, and we offer customers a range of services including product and systems design, automation, fabrication, assembly, and large volume contract manufacturing. Our customers span a wide array of industries including aerospace, defense, mobility, healthcare, pharma, biotech, clean tech, chemicals, energy, lifestyle, food production, and industrial equipment.
The BIG payoff
We are a company who is going to make a difference in the industries and the communities in which we choose to operate. Every employee of Re:Build will share ownership in the company and will share in the financial rewards of the success we achieve together, at all levels of the company! We want to work with people that reflect the communities in which we operate
Re:Build Manufacturing is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, veteran status, marital status, parental status, cultural background, organizational level, work styles, tenure and life experiences. Or for any other reason.
Re:Build is committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need assistance or an accommodation due to a disability, you may contact us at accommodations.ta@ReBuildmanufacturing.com or you may call us at 617.909.6275.
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Machine Learning Fellow - Human Frontier Collective (US)
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PLEASE NOTE: This is a fully remote, 1099 independent contractor opportunity with an estimated duration of six months and the potential for extension. To be eligible, candidates must be authorized to work in the United States; visa sponsorship is not available for this role.
About the Program
The Human Frontier Collective (HFC) Fellowship brings together top researchers and domain experts to collaborate on high-impact work that are shaping the future of AI. As an HFC Fellow, you’ll apply your academic and professional expertise to help design, evaluate, and interpret advanced generative AI systems—while gaining exposure to cutting-edge research and working alongside an interdisciplinary network of leading thinkers.
What You'll Do
- ML Projects: Get invited to engage in high-impact projects with our partnered AI labs and platforms. Help models understand real-world deep learning workflows by designing, reviewing, and optimizing PyTorch models, evaluating complex ML code and AI-generated implementations for efficiency and correctness, and advising on GPU optimization, scaling, and trade-offs.
- HFC Community: Beyond the work, you’ll become part of a supportive, interdisciplinary network of innovators and thought leaders committed to advancing frontier AI across domains.
- Contribute to Research Publications: Collaborate with Scale’s research team to co-author technical reports and research papers—boosting your academic visibility and professional recognition (e.g., SciPredict, PropensityBench, Professional Reasoning Benchmark).
Who Should Apply
- Education: PhD or postdoctoral degree in Computer Science, Computer Engineering, or a related field.
- Professional Background: 1-3+ years of experience as a Machine Learning Engineer or Data Scientist.
- Skills: Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow). Experience with cloud infrastructure (AWS) and MLOps tools (Docker, Langchain) is a plus.
- Professional Mindset: Detail-oriented, innovative thinker with a passion in applied AI research and a commitment to collaboration.
Why Join the HFC?
- Professional Development: High-impact experts expand their influence through review projects, advisory roles, and research, while deepening their AI expertise, strengthening analytical and problem-solving skills, and engaging with pioneering AI applications in science and technology.
- Join a Top-Tier Network: Collaborate with a global network of engineers and experts to advance responsible AI through impactful, flexible research and training. 80% of our members come from leading institutions.
- Flexible Schedule: Set your own schedule, with flexible 10–40 hour weeks that fit around your life and other commitments.
- Competitive Pay: Project pay rates vary across platforms and are depending on a number of factors, including but not limited to; projects, scope, skillset, and location.
Application Process
- Apply: We review applications on a rolling basis.
- Interview: Candidates will get to discuss their research experience, professional background, and alignment with our mission to advance human-centered AI.
- Join the Collective: Successful candidates will receive an invitation to join the Human Frontier Collective Fellowship.
PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.
About Us:
At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.
We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.
We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information.
We comply with the United States Department of Labor's Pay Transparency provision.
PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
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AI is rapidly transforming the world. As generative AI reshapes industries, teams need powerful ways to monitor, troubleshoot, and optimize their AI systems. That’s where we come in. Arize AI is the leading AI & Agent Engineering observability and evaluation platform, empowering AI engineers to ship high-performing, reliable agents and applications. From first prototype to production scale, Arize AX unifies build, test, and run in a single workspace—so teams can ship faster with confidence.
We’re a Series C company backed by top-tier investors, with over $135M in funding and a rapidly growing customer base of 150+ leading enterprises and Fortune 500 companies. Customers like Booking.com, Uber, Siemens, and PepsiCo leverage Arize to deliver AI that works.
The Team
Our engineering team builds systems that interact with some of the most complex software ever deployed in production. The team is composed of industry veterans that have built deep learning infrastructure, autonomous drones, ridesharing marketplaces, ad tech and much more. We are looking for an AI Sales Engineer (Solutions Architect) to join the good fight and get this product in the hands of every AI/ML organization.
You'll work side-by-side with our Account Executives to articulate the Arize value and overall strategy to differentiate the platform throughout the sales process and drive POCs from requirements gathering to close. The activities performed by an AI Sales Engineer are diverse - one day you might be assisting with a high-level pitch of Arize to a CDO, and the next day you might be working hands-on to develop a small proof of concept.
What You’ll Do
You are the trusted advisor to the customer:
- Partner with our account executives to articulate the overall Arize value proposition, vision, and strategy to customers
- Work closely with some of the most sophisticated GenAI teams in the world.
- You will act as a trusted advisor to our prospective customers, while also building relationships with technical and business stakeholders.
- Lead product demonstrations of the Arize platform
- Advise on GenAI and ML best practices
- Lead discovery to understand prospect’s GenAI tech stack to collaborate with the Sales team to construct a compelling value proposition of the Arize Platform
- Lead Proof of Concept (PoC) motions with prospective buyers
- Handle technical objections and develop strategies across sales, engineering, and product to unblock them
What We’re Looking For
Note: Even if you do not check every single box, we still encourage you to apply!
- 3+ years of experience in a customer-facing role such as sales engineer, solutions engineer, or forward deployed engineer
- Strong communication skills: Ability to simplify complex, technical concepts
- Proficiency in Python / Typescript
- Knowledge of LLM / Agentic frameworks such as OpenAI Agents SDK, Google ADK, LangGraph, and DSPy
- Understanding of GenAI concepts and application evaluation + development lifecycle
- A quick and self learner - undaunted by technical complexity of production AI deployments and welcome the challenge to learn about them and develop your own POV.
Bonus Points, But Not Required
- Previous experience working across and aligning Sales, Product, and Engineering
- Previous experience within a team that underwent a high growth stage
- Previous engineering experience in: Data Engineering, MLOps, Kubernetes, GCP / AWS / Azure
The estimated annual salary and variable compensation for this role is between $140,000 - $230,000, plus a competitive equity package. Actual compensation is determined based upon a variety of job related factors that may include: transferable work experience, skill sets, and qualifications. Total compensation also includes a comprehensive benefit package, including: medical, dental, vision, 401(k) plan, unlimited paid time off, generous parental leave plan, and others for mental and wellness support.
While we are a remote-first company, we have opened offices in New York City and the San Francisco Bay Area, as an option for those in those cities who wish to work in-person. For all other employees, there is a WFH monthly stipend to pay for co-working spaces.
More About Arize
Arize’s mission is to make the world’s AI work—and work for people.
Our founders came together through a shared frustration: while investments in AI are growing rapidly across every industry, organizations face a critical challenge—understanding whether AI is performing and how to improve it at scale.
Learn more about what we're doing here:
https://techcrunch.com/2025/02/20/arize-ai-hopes-it-has-first-mover-advantage-in-ai-observability/
Diversity & Inclusion @ Arize
Our company's mission is to make AI work and make AI work for the people, we hope to make an impact in bias industry-wide and that's a big motivator for people who work here. We actively hope that individuals contribute to a good culture
- Regularly have chats with industry experts, researchers, and ethicists across the ecosystem to advance the use of responsible AI
- Culturally conscious events such as LGBTQ trivia during pride month
- We have an active Lady Arizers subgroup
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Staff Machine Learning Research Scientist
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SmarterDx, a Smarter Technologies company, builds clinical AI that is transforming how hospitals translate care into payment. Founded by physicians in 2020, our platform connects clinical context with revenue intelligence, helping health systems recover millions in missed revenue, improve quality scores, and appeal every denial. Become a Smartian and help optimize the way the healthcare system works for everyone. Learn more at smarterdx.com/careers.
As a Staff Machine Learning Research Scientist at SmarterDx, you will set technical direction for cutting-edge ML research and translate it into real-world clinical impact. You’ll work at the intersection of research, engineering, and healthcare, partnering with engineers and clinicians to build systems that deeply understand patient records and improve hospital outcomes. This is a senior, high-impact role where you’ll not only execute on ambitious ideas but also shape the team’s research agenda and standards.
You will be expected to operate with a high degree of autonomy—identifying promising research directions, critically evaluating academic work, and ensuring that what gets built is both scientifically sound and practically useful. Your work will directly influence how we evaluate models, detect hallucinations, and build high-quality datasets, ultimately improving the reliability of AI in healthcare.
**This role is fully remote within the US**
What You’ll Do
- Lead end-to-end ML research, from idea generation to production deployment and monitoring
- Design, implement, and evaluate novel methods for LLM alignment on proprietary clinical data
- Develop and rigorously evaluate approaches for hallucination detection, attribution, and model reliability
- Build and curate high-quality datasets, with a strong emphasis on evaluation design and benchmark integrity
- Critically assess academic literature to identify strong vs weak methods, and translate the best ideas into practice
- Establish best practices for experimental design, including statistically sound evaluation and reproducibility
- Collaborate cross-functionally with engineering to productionize models (MLOps, infra, deployment)
- Develop methods for long-context and multimodal modeling (structured + unstructured clinical data)
- Mentor other researchers and help raise the bar for research quality across the team
- Contribute to external presence through papers, talks, and recruiting
What You Bring
- Strong track record of ML research, ideally with publications in top-tier venues (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, AAAI, etc.)
- Proven ability to distinguish high-quality vs low-quality research, especially in fast-moving areas like LLMs
- Deep understanding of LLM failure modes, particularly hallucinations, and how to evaluate and mitigate them
- Experience designing rigorous evaluation frameworks and building high-quality test datasets
- Strong intuition for dataset quality, bias, and benchmark design (data-centric AI mindset)
- Hands-on experience training large-scale deep learning models (multi-GPU / distributed systems)
- Deep understanding of modern neural architectures (transformers, SSMs, encoder/decoder models, etc.)
- Strong programming skills in Python and ML frameworks such as PyTorch or JAX
- Experience deploying ML models into production systems and monitoring their performance
- Clear and proactive communicator, able to explain complex ideas and critique work effectively
Nice To Haves
- Experience with inference optimization techniques (e.g., vLLM, KV caching, speculative decoding)
- Familiarity with MLSys concepts (parallelism strategies, distributed training infrastructure)
- Experience working with clinical or healthcare data
- Background in retrieval systems, graph-based learning, or multimodal modeling
Our Tech Stack
- PyTorch, Hugging Face Transformers, Python
- AWS (MWAA), Kubernetes, SLURM
- DeepSpeed, TorchTune
- Snowflake, Airflow, GitHub
Compensation
$220k-260k base salary
#LI-Remote
Benefits
- Medical, Dental & Vision – Comprehensive plans with leading insurance providers, covering 75% of your premiums, depending on the plan.
- Paid Parental Leave – Generous paid leave to support families through birth or adoption: Up to 12 weeks for parents.
- Remote-First Team – Work from anywhere in the U.S.
- Unlimited PTO & 10 Holidays – So you can relax and recharge.
- 401(k) with Traditional & Roth Options – Tax-advantaged retirement savings through Fidelity with a 4% match.
- Minimal Bureaucracy – A fast-moving, high-impact environment where you can focus on what matters.
- Incredible Teammates! – Work alongside smart, supportive, and mission-driven colleagues.
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Apply to SmarterDxSenior Machine Learning Research Scientist
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SmarterDx, a Smarter Technologies company, builds clinical AI that is transforming how hospitals translate care into payment. Founded by physicians in 2020, our platform connects clinical context with revenue intelligence, helping health systems recover millions in missed revenue, improve quality scores, and appeal every denial. Become a Smartian and help optimize the way the healthcare system works for everyone. Learn more at smarterdx.com/careers.
Role
As a Machine Learning Research Scientist, you will lead groundbreaking ML research and development at SmarterDx, collaborating closely with experienced engineers and clinicians to turn your inventions into enterprise-grade products. With minimal supervision, you will establish a research agenda informed by emerging trends in AI, develop and rigorously evaluate your proposed algorithms, deploy your algorithms into production, and monitor impact. You will collaborate closely with other machine learning research scientists to identify the most promising areas of AI/ML R&D for SmarterDx and establish shared infrastructure to accelerate research efforts across the team.
What You'll Do
- 45% Hands-on implementing new methods and relevant baseline models (ML Research)
- 20% Working cross-functionally to deploy models into production (MLOps, MLE)
- 20% Data Science (data engineering, dataset curation, experimental design, model updates, product domain expertise)
- 15% Academics & Outreach (e.g., scientific reading & writing, publishing, presenting at conferences, recruiting)
- Become a domain expert at clinical data and the healthcare ecosystem
- Own end to end model development including deployment into production and production monitoring, learning Machine Learning Operations (MLOps)
- Post training to align large language models (LLMs) on proprietary clinical data
- Develop new self-supervised pre-training tasks for improving models
- Develop novel retrieval, attribution and hallucination detection strategies for generative models
- Develop novel methods for explaining and summarizing diagnostic classifications
- Develop methods for selecting data sources to include in training (data-centric AI)
- Develop novel graph-based algorithms for improving classification of diseases and procedures with few or no labels
- Develop novel methods for multimodal data fusion (structured and unstructured data)
- Long-sequence language modeling
What You Bring
- Desire to translate research into tangible positive impact by deploying research into production engineering systems (MLOps)
- With scientific concepts, technical debugging or domain knowledge, ability and desire to communicate clearly and proactively when conveying or receiving
- Deep “under-the-hood” understanding of modern neural network architectures and distributed training. ie knows the differences between SwiGLU vs. sigmoid, GRUs vs. transformers vs SSMs, encoders vs. decoders, masked language models vs. autoregressive language models, Megatron vs nanotron vs DeepSpeed
- Extensive experience developing, implementing and training state-of-the-art deep learning models using multiple GPUs and nodes if necessary for large language models with frameworks such as PyTorch, JAX, etc
- Ability to assess, understand and create high-quality machine learning research, as demonstrated through publications at top-tier conferences and journals (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, SIGIR, AAAI, NEJM AI, JAMIA, npj Digital Medicine, arXiv)
Nice To Haves
- MLSys skills ie knows the differences between tensor vs pipeline vs data parallelism, gloo vs mpi vs nccl, CUDA vs ROCm, Triton vs ThunderKittens
- Familiarity with inference optimizations, ie vLLM, SGLang, continuous batching, KV Caching, speculative decoding
Our Tech Stack
- PyTorch, Python, GitHub, Snowflake, Huggingface Transformers, AWS Sagemaker, Microsoft DeepSpeed, TorchTune, Apache Airflow, SLURM, Kubernetes
Compensation
$200-220k+ base salary
#LI-Remote
#LI-DNP
Benefits
- Medical, Dental & Vision – Comprehensive plans with leading insurance providers, covering 75% of your premiums, depending on the plan.
- Paid Parental Leave – Generous paid leave to support families through birth or adoption: Up to 12 weeks for parents.
- Remote-First Team – Work from anywhere in the U.S.
- Unlimited PTO & 10 Holidays – So you can relax and recharge.
- 401(k) with Traditional & Roth Options – Tax-advantaged retirement savings through Fidelity with a 4% match.
- Minimal Bureaucracy – A fast-moving, high-impact environment where you can focus on what matters.
- Incredible Teammates! – Work alongside smart, supportive, and mission-driven colleagues.
Ready to apply?
Apply to SmarterDx
Senior Machine Learning (ML) Engineer
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Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.
ABOUT THE TEAM
Anduril's Air & Missile Defense Radar team develops cutting-edge tracking algorithms and software systems that detect, track, and characterize airborne threats in real-time. We're building the next generation of tracking intelligence capabilities—automated analysis systems that understand tracking performance, identify failure modes, and continuously improve our algorithms through data-driven insights.
This role sits at the intersection of ML engineering and tracking domain expertise. You'll build end-to-end pipelines that ingest tracking algorithm telemetry, analyze correlation failures and performance anomalies, train models to automate root cause analysis, and deploy production tools that help engineers ask questions like "why didn't track X and track Y associate?" We don't just track targets; we track our tracking systems and make them smarter.
WHAT YOU'LL DO
- Own tracking intelligence infrastructure end-to-end: Build the platform for ingesting tracking algorithm telemetry (hypotheses, scores, gains, association decisions), feature engineering performance metrics, training analysis models, and deploying them into production
- Automate tracking analysis: Develop ML models that identify correlation failures, track quality degradation, and root causes for tracking anomalies—replacing manual deep-dive investigations with scalable automated insights
- Build autotuning capabilities: Create systems that recognize incoming data characteristics and automatically adjust tracking algorithm parameters, frame rates, and model configurations for optimal performance
- Design human-in-the-loop tools: Build interfaces and query services that let engineers ask natural questions about tracking behavior and get data-driven answers backed by your models
- Exploit tracking telemetry: Instrument C++ tracking algorithms with appropriate logging (working with platform engineers), then marshal that data into consistent formats for analysis and model training
- Deploy in constrained environments: Package and deploy models for air-gapped systems with no external connectivity, following security scanning requirements where ML models are treated as data artifacts
- Manage the ML lifecycle: Handle data catalogs, ground truth labeling, model registries, versioning, and validation—ensuring models improve tracking performance in measurable ways
- Bridge domains: Translate between tracking algorithm fundamentals (Kalman filters, data association, multi-hypothesis tracking) and ML/data science techniques to build solutions that actually work
- Drive make/build decisions: Evaluate when to build custom models vs. leverage existing ML capabilities, selecting appropriate algorithm architectures for tracking intelligence problems
- Work hands-on-keyboard: This is a one-person show initially—you'll architect, code, deploy, and iterate rapidly using modern Python-based ML tooling
REQUIRED QUALIFICATIONS
- 3+ years of experience with a strong mix of ML engineering and data science—you've built models AND deployed them into production systems
- Proficiency in Python and modern ML frameworks (PyTorch, TensorFlow, scikit-learn)
- Experience with MLOps practices: data pipelines, feature engineering, model versioning, experiment tracking, and deployment workflows
- Familiarity with ML infrastructure tooling (MLflow, Dagster/Airflow, or similar orchestration tools)
- Understanding of tracking, estimation, or filtering algorithms (Kalman filters, data association techniques)—you need to understand what tracking algorithms output and why they make the decisions they do
- Ability to work with streaming time-series data and engineer features from algorithm telemetry
- Experience building data catalogs, managing ground truth labels, and validating model performance
- Strong software engineering fundamentals—you can build maintainable, production-quality code independently
- Comfortable working in C++ environments enough to add instrumentation/logging (no deep algorithm development required)
- Ability to obtain and maintain a U.S. Top Secret SCI security clearance
PREFERRED QUALIFICATIONS
- Experience deploying ML models in edge, embedded, or air-gapped environments with security constraints
- Background in defense, aerospace, or sensor systems
- Familiarity with containerization (Docker, Kubernetes) for model serving and deployment
- Experience with anomaly detection, root cause analysis, or automated diagnostics systems
- Knowledge of AutoML, hyperparameter tuning, or online learning techniques
- Understanding of radar systems, sensor fusion, or signal processing
- Experience building conversational or query interfaces for technical systems
- Familiarity with model registries and model-as-data artifact management
- Experience with distributed data processing (Spark, Dask) for large-scale telemetry analysis
- Formal coursework or training in MLOps, data science, or estimation theory
- Active U.S. Top Secret SCI clearance
We request transcripts as part of the early application process to understand your academic background and how your coursework supports the skills deemed critical for the role. Transcripts help us assess your technical and analytical abilities, complementing our interview process in which we also evaluate practical experience and cultural fit. If you choose not to share your transcripts, you will need to provide detailed information regarding your academic performance in relevant courses, including projects and coursework specifics, to ensure we evaluate your academic accomplishments properly. If you do provide academic transcripts, feel free to redact non-technical information (e.g., student ID, dates, non-technical coursework, etc.). Unofficial transcripts obtained online acceptable for this assessment.
The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. Highly competitive equity grants are included in the majority of full time offers; and are considered part of Anduril's total compensation package. Additionally, Anduril offers top-tier benefits for full-time employees, including:
Benefits
At Anduril, we invest in our people. Our comprehensive, competitive benefits package (available at little to no cost to employees) ensures you’re supported in health, recovery, and whatever comes next. For more information, Explore Our Benefits.
Protecting Yourself from Recruitment Scams
Anduril is committed to maintaining the integrity of our Talent acquisition process and the security of our candidates. We've observed a rise in sophisticated phishing and fraudulent schemes where individuals impersonate Anduril representatives, luring job seekers with false interviews or job offers. These scammers often attempt to extract payment or sensitive personal information.
To ensure your safety and help you navigate your job search with confidence, please keep the following critical points in mind:
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No Financial Requests: Anduril will never solicit payment or demand personal financial details (such as banking information, credit card numbers, or social security numbers) at any stage of our hiring process. Our legitimate recruitment is entirely free for candidates.
- Please always verify communications:
- Direct from Anduril: If you receive an email from one of our recruiters, it will only come from an
@anduril.comaddress. - Via Agency Partner: If contacted by a recruiting agency for an Anduril role, their email will clearly identify their agency. If you suspect any suspicious activity, please verify the agency's authenticity by reaching out to contact@anduril.com.
- Direct from Anduril: If you receive an email from one of our recruiters, it will only come from an
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Exercise Caution with Unsolicited Outreach: If you receive any communication that appears suspicious, contains grammatical errors, or makes unusual requests, do not engage. Always confirm the sender's email domain is @anduril.com before providing any personal information or clicking on links.
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What to Do If You Suspect Fraud: Should you encounter any questionable or fraudulent outreach claiming to be from Anduril, please report it immediately to contact@anduril.com. Your proactive caution is invaluable in protecting your personal information and upholding the security and trustworthiness of our recruitment efforts.
Data Privacy
To view Anduril's candidate data privacy policy, please visit https://anduril.com/applicant-privacy-notice/.
By submitting your application, you consent to Anduril Industries using a third-party service provider to conduct pre-employment risk, integrity, and due diligence screening and assessing potential risks as part of your application process. This third-party service provider provides risk-intelligence services that may include analysis of sanctions and watchlists, adverse media, public-record information, and other lawful open-source or commercial data sources. This third-party service provider does not act as a consumer reporting agency. Use of this provider helps to ensure compliance with applicable laws and protect technology, intellectual property, and organizational security.
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Machine Learning and AI Opportunities
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About Us
SharkNinja is a global product design and technology company, with a diversified portfolio of 5-star rated lifestyle solutions that positively impact people’s lives in homes around the world. Powered by two trusted, global brands, Shark and Ninja, the company has a proven track record of bringing disruptive innovation to market and developing one consumer product after another has allowed SharkNinja to enter multiple product categories, driving significant growth and market share gains. Headquartered in Needham, Massachusetts with more than 4,100 associates, the company’s products are sold at key retailers, online and offline, and through distributors around the world.
Note: This is a Pipeline Opening and Not Tied to A Specific Opening
The AI Product Manager owns strategy, roadmap, and delivery for AI initiatives across the enterprise. This role translates business objectives into a clear prioritized backlog, collaborating with engineering teams and external partners to deliver impactful solutions that drive measurable business impact through revenue growth or new operational efficiencies. The Product Manager works closely with Global Data Product Management, including Data and MDM, to ensure AI products are built on trusted, standardized data foundations. The role requires strong judgment in application integrations and build vs. buy tradeoffs, balancing speed, cost, and enterprise standards.
Key Responsibilities
|
Area |
What You’ll Own |
|
Product Strategy & Vision |
Define a 3–9-month AI roadmap aligned to company strategic goals, with clear problem statements and value hypotheses to maximize value. |
|
Portfolio & Roadmap |
Convert strategy into prioritized increments with PRDs, acceptance criteria, and release plans; keep a transparent backlog. |
|
Evaluation & Experimentation |
Own evaluation for AI features: offline tests, human and automated evals, and online A/B experiments to optimize quality, latency, and cost effectiveness. Publish decision logs for model, prompt, and dataset changes. |
|
Responsible AI & Guardrails |
Define safety, privacy, and compliance requirements; implement guardrails and review rituals with Security and Legal; ensure traceability of data, prompts, and outputs. |
|
Application Integrations |
Define product requirements for API-first and event driven integrations across CRM/ERP/eCommerce and data platforms; align on data contracts, SLAs, auth/PII handling, and system observability with Platform teams. |
|
Build vs Buy |
Lead structured tradeoff analyses (TTV, TCO, vendor lock in, differentiation, compliance). Run proofs of value with vendors when needed and recommend paths forward, highlighting risks and contingency plans.. |
|
Cross‑Functional Leadership |
Lead squads spanning ML Engineering, MLOps, Data Engineering, Analytics, and Business stakeholders; keep scope, risks, and dependencies visible. |
|
Impact Measurement |
Define clear KPIs that connect business outcomes to product performance, and provide executives with simple, actionable reporting against those targets. |
|
Partnerships |
Collaborate with Director, ML and AI, Security, Legal, Procurement, and Global Data Product Management (Data and MDM) to align standards, governance, and delivery. |
Required Qualifications
- 5+ years in product management with shipped data or AI features tied to measurable outcomes.
- Proven ownership of evaluation and experimentation for AI features (offline metrics, human/auto evals, and A/B testing).
- Handson experiences driving application integrations at enterprise scale (APIled and iPaaS patterns, SLAs, data contracts, identity).
- Demonstrated ability to lead build vs. buy decisions, supported by clear financial models and risk analyses.
- Excellent executive communication and stakeholder leadership.
Preferred Qualifications
- Experience optimizing Amazon sales and ad channels.
- Experience with Salesforce Cloud and CDP integrations.
- Exposure to LLMOps practices (prompt versioning, guardrails, eval frameworks), vector search/RAG, or model observability.
Success Metrics (first 12 months)
- AI roadmap approved and in execution within 90 days.At least two AI product increments shipped with adoption targets met.
- Application integrations delivered on time with measurable data quality and reliability improvements.
- At least two major technology decisions completed with a formal build vs. Buy analysis and exec approval.
- AI initiatives deliver a minimum 5x ROI on Capex investments, contributing directly to revenue growth.
Salary and Other Compensation: The annual salary range for this position is displayed below. Factors which may affect starting pay within this range may include geography/market, skills, education, experience and other qualifications of the successful candidate.
The Company offers the following benefits for this position, subject to applicable eligibility requirements: medical insurance, dental insurance, vision insurance, flexible spending accounts, health savings accounts (HSA) with company contribution, 401(k) retirement plan with matching, employee stock purchase program, life insurance, AD&D, short-term disability insurance, long-term disability insurance, generous paid time off, company holidays, parental leave, identity theft protection, pet insurance, pre-paid legal insurance, back-up child and eldercare days, product discounts, referral bonus program, and more.
Our Culture
At SharkNinja, we don’t just raise the bar—we push past it every single day. Our Outrageously Extraordinary mindset drives us to tackle the impossible, push boundaries, and deliver results that others only dream of. If you thrive on breaking out of your swim lane, you’ll be right at home.
What We Offer
We offer competitive health insurance, retirement plans, paid time off, employee stock purchase options, wellness programs, SharkNinja product discounts, and more. We empower your personal and professional growth with high impact Learning Programs featuring bold voices redefining what’s possible. When you join, you’re not just part of a company—you’re part of an outrageously extraordinary community. Together, we won’t just launch products—we’ll disrupt entire markets.
At SharkNinja, Diversity, Equity, and Inclusion are vital to our global success. Valuing each unique voice and blending all of our diverse skills strengthens SharkNinja’s innovation every day. We support ALL associates in bringing their authentic selves to work, making an impact, and having the opportunity for career acceleration. With help from our leadership, associates, and our community, we aim to have equity be a key component of the SharkNinja DNA.
Learn more about us:
Life At SharkNinja
Outrageously Extraordinary
SharkNinja Candidate Privacy Notice
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For candidates based in all regions, please refer to this Candidate Privacy Notice.
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For candidates based in China, please refer to this Candidate Privacy Notice.
-
For candidates based in Vietnam, please refer to this Candidate Privacy Notice.
We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, disability, or any other class protected by legislation, and local law. SharkNinja will consider reasonable accommodations consistent with legislation, and local law. If you require a reasonable accommodation to participate in the job application or interview process, please contact SharkNinja People & Culture at accommodations@sharkninja.com
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RVP, Enterprise Sales
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About Nebius:
Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.
Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.
Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.
The team
Nebius is building a world-class commercial organization to match the scale of our infrastructure platform. Our GTM leadership team operates with high trust, direct access to Product and Engineering, and the mandate to define how Nebius competes and wins in the enterprise. You will join a senior leadership bench that values clarity, accountability, and speed — with fewer layers and more impact than the hyperscalers.
The role
Nebius is seeking an Enterprise Sales Leader to build and scale our industry go-to-market across priority verticals including Financial Services, Healthcare & Life Sciences, Manufacturing, Media & Entertainment, Automotive, and Energy.
This leader will:
- Build a verticalized enterprise sales motion
- Lead a team of Enterprise AEs aligned to industry segments
- Drive repeatable, multi-year AI infrastructure deals
- Operationalize a partner-led GTM model anchored in NVIDIA and strategic SIs
Success in this role requires combining vertical expertise, ecosystem orchestration, and enterprise deal execution to establish Nebius as the AI infrastructure platform of choice.
Success will be measured not only by direct revenue, but by partner-influenced pipeline, multi-year capacity commitments, and lighthouse customer acquisition.
You are welcome to work remotely from the US.
Partner & NVIDIA Motion
This role will lead a partner-centric enterprise GTM model:
- Own joint go-to-market with NVIDIA field teams across priority verticals
- Build and scale co-sell motions with SIs and channel partners (Accenture, Deloitte, Slalom, CDW, WWT, etc.)
- Enable ISVs to embed Nebius into enterprise workflows and solutions
- Drive partner-sourced and partner-influenced pipeline as a core KPI
- Establish joint value propositions combining infrastructure + software + services
Your responsibilities will include:
- Define and execute vertical-specific GTM strategies aligned to NVIDIA’s top enterprise markets.
- Hire, develop, and lead a team of Enterprise Account Executives focused on industry specialization — setting performance standards, coaching deal execution, and driving vertical expertise.
- Own revenue targets and ARR growth across assigned verticals.
- Develop named account strategies within priority enterprise segments.
- Personally engage in complex, multi-million-dollar GPU infrastructure deals — connecting infrastructure decisions to vertical-specific business outcomes.
- Build executive-level relationships across CIO, CTO, Chief Data, and Line-of-Business leaders.
- Collaborate closely with NVIDIA field teams to drive joint account planning and pipeline development.
- Establish forecasting rigor, pipeline discipline, and enterprise sales standards across the vertical portfolio.
- Partner cross-functionally with CSA, Product, Marketing, Capacity Planning, and Partnerships to align resources and deliver differentiated value.
- Drive land-and-expand motions across AI training, inference, and production AI workloads.
- Evangelize Nebius’s NVIDIA-based GPU platform (H100, H200, B200, GB200 NVL72, and beyond) within vertical-specific use cases.
- Build vertical-specific solution plays (RAG, training, inference, MLOps) with partners
- Drive partner-led access to enterprise buying centers (CIO, CDAO, CISO, ML teams)
- Scale 1:few and 1:many partner GTM programs (not just direct selling)
- Establish lighthouse customers per vertical
We expect you to have:
- 10+ years of enterprise infrastructure or cloud sales experience, with a proven track record in one or more large enterprise verticals.
- 5+ years of leadership experience managing enterprise sales teams with vertical or industry specialization.
- Proven success closing $5M–$50M+ infrastructure or platform deals within regulated or complex industry segments.
- Strong understanding of vertical-specific AI use cases, regulatory environments, and enterprise buying cycles.
- Experience co-selling with strategic ecosystem partners (e.g., NVIDIA, OEMs, SIs) and navigating partner-driven motions.
- Builder mindset — you’ve created vertical-focused GTM playbooks, coverage models, and scalable sales motions where none existed.
- Demonstrated ability to build and scale vertical-focused sales teams within high-growth companies.
- High energy, ownership mentality, and consistent overachievement against targets.
- Experience co-selling with NVIDIA and/or large SIs in enterprise environments
- Proven ability to drive partner-influenced enterprise revenue at scale
- Deep understanding of enterprise procurement + partner-driven buying cycles
It will be an added bonus if you have:
- Direct experience working with NVIDIA field teams or ecosystem partners on enterprise sales motions.
- Experience selling AI/ML infrastructure into regulated or highly complex industries (e.g., FSI, Healthcare, Energy).
- Background in hyperscaler, neo-cloud, or GPU-first environments.
- Established executive network within one or more priority enterprise verticals.
- Experience structuring multi-year infrastructure and capacity commitments.
- Prior leadership at a hyperscaler or neo-cloud (e.g., AWS, Azure, GCP, CoreWeave, Lambda).
Key Employee Benefits
- Health Insurance: 100% company-paid medical, dental, and vision coverage for employees and families.
- 401(k) Plan: Up to 4% company match with immediate vesting.
- Parental Leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers.
- Remote Work Reimbursement: Up to $85/month for mobile and internet.
- Disability & Life Insurance: Company-paid short-term, long-term, and life insurance coverage.
Compensation
We offer competitive salaries in the 458K - 550K range + equity
Don’t just work in tech. Shape it. If you’re driven to define how the world builds with AI, we want to hear from you.
Benefits & Perks:
- Competitive compensation
- Career growth and learning opportunities
- Flexibility and work-life balance
- Collaborative and innovative culture
- Opportunity to work on impactful AI projects
- International environment and talented teams
What's it like to work at Nebius:
Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI
Equal Opportunity Statement:
Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.
Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire.
If you need accommodations during the application process, please let us know.
Ready to apply?
Apply to Nebius
About Nebius:
Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.
Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.
Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.
Customer experience:
Customer experience at Nebius AI Cloud involves tackling customers’ challenges and directly impacting their success by solving real-world AI and ML problems at massive GPU cloud scale. You’ll not only resolve issues, but play a key role in shaping clients’ business success by optimizing their AI solutions. Working with advanced GPUs such as H200, B200 and GB200, as well as modern ML frameworks, you’ll influence the development of the Nebius AI Cloud and gain experience at the intersection of infrastructure and AI. With minimal bureaucracy, you’ll have the freedom to innovate, take ownership and drive change. Opportunities for growth are abundant in this vibrant and supportive professional community.
The role
We are seeking a Specialist HPC Infrastructure Solutions Architect to design, build, and optimize next-generation high-performance computing (HPC) platforms for AI, simulation, and large-scale data processing workloads. The ideal candidate combines deep knowledge of cloud-native architecture, Kubernetes orchestration, networking, and HPC system design with hands-on experience implementing NVIDIA GPU-based compute environments and MLOps toolchains. This role sits at the intersection of infrastructure engineering, accelerated computing, and AI systems design, shaping the foundation for high-throughput, low-latency distributed workloads in cloud environment.
You’re welcome to work remotely from the United States or Canada.
Your responsibilities will include:
- Architect and implement scalable HPC clusters optimized for AI, simulation, and distributed training, leveraging container orchestration frameworks and schedulers (e.g., Kubernetes, Slurm).
- Design and integrate GPU-accelerated compute infrastructures featuring NVIDIA Hopper, Blackwell architectures, NVLink/NVSwitch, and InfiniBand/RoCE Interconnects.
- Deploy, and manage GPU Operator and Network Operator stacks for automated lifecycle management of GPU and high-speed networking components.
- Design and validate cloud HPC environments, focusing on low-latency, high-bandwidth networking, multi-GPU scaling, and efficient workload scheduling.
- Lead reference architectures for AI/ML model training, data pipelines, and MLOps integrations using modern observability and CI/CD tooling.
- Collaborate with hardware vendors (e.g., NVIDIA) and cloud providers to evaluate and optimize emerging HPC and GPU technologies.
- Benchmark system performance, identify bottlenecks, and tune resource utilization across compute, network, and storage tiers.
- Provide expert-level technical guidance to customers, internal teams, and partners on HPC architecture patterns, operational excellence reviews and customer engagements
We expect you to have:
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field (Ph.D. a plus)
- 3+ years of hands-on experience architecting HPC or large-scale GPU clusters.
- Expertise in Linux systems, Kubernetes, container runtimes (containers, CRI-O, Docker), and related CI/CD practices.
- Strong understanding of HPC networking protocols and RDMA stacks (InfiniBand, NVLink/NVSwitch)
- Deep understanding of storage and I/O optimization for large datasets (Ceph, Lustre, NFS, GPUDirect Storage)
- Familiarity with Terraform, Ansible, Helm, and GitOps workflows.
- Strong scripting skills in Python or Bash for automation and tool integration.
- Excellent communication and documentation skills; ability to lead design
- reviews and customer engagements
It will be an added bonus if you have:
- Proficient with NVIDIA GPU ecosystem: GPU Operator, MIG, DCGM, NCCL, Nsight, and CUDA stack management.
- Experience designing or managing AI/ML pipelines via MLflow, Kubeflow, NeMo, or similar frameworks.
- Experience with cloud-native HPC offerings (Slurm, LFS, PBS, etc.).
- Background in designing multi-tenant GPU infrastructures or AI training farms.
- Exposure to distributed ML frameworks (PyTorch DDP, DeepSpeed, Megatron).
- Knowledge of observability for HPC (Prometheus, DCGM Exporter, Grafana, NVIDIA NGC monitoring tools)
- Contribution to open-source HPC/CUDA/Kubernetes projects is a strong plus
Key Employee Benefits:
- Health Insurance: 100% company-paid medical, dental, and vision coverage for employees and families.
- 401(k) Plan: Up to 4% company match with immediate vesting.
- Parental Leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers.
- Remote Work Reimbursement: Up to $85/month for mobile and internet.
- Disability & Life Insurance: Company-paid short-term, long-term, and life insurance coverage.
Compensation
We offer competitive salaries, ranging from 225k - 315k OTE (On-Target Earnings) and equity based on your experience, skills, and location.
Join Nebius Today!
Benefits & Perks:
- Competitive compensation
- Career growth and learning opportunities
- Flexibility and work-life balance
- Collaborative and innovative culture
- Opportunity to work on impactful AI projects
- International environment and talented teams
What's it like to work at Nebius:
Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI
Equal Opportunity Statement:
Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.
Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire.
If you need accommodations during the application process, please let us know.
Ready to apply?
Apply to Nebius
About Nebius:
Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.
Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.
Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.
The role
We seek an experienced Senior ML Solutions Architect to support customers leveraging Nebius Token Factory's serverless inference platform for open-source LLMs across multiple modalities. In this role, you will be collaborating with clients to design and implement customized LLM-based solution and architect scalable AI applications using our served models, and working together with our backend team to improve our platform to match the clients' needs.
Your responsibilities will include:
- Design and implement LLM-based solutions using Nebius Token Factory’s inference services to drive business value and support customer goals.
- Build production-ready applications leveraging our serverless LLM APIs, including multimodal models (text, vision, audio) and domain-specific models.
- Provide technical expertise in prompt engineering, RAG architectures, model selection, and inference optimization.
- Collaborate with product and engineering teams to surface customer feedback and shape the platform roadmap.
- Guide customers in scaling from POC to production with a focus on performance, reliability, and cost efficiency.
We expect you to have:
- 5+ years of experience in ML/AI systems, with at least 2 years focused on LLMs and generative AI.
- Deep knowledge of the LLM ecosystem, including model architectures and fine-tuning approaches.
- Hands-on experience with:
- Prompt engineering and LLM pipeline development, including evaluation.
- Agentic frameworks such as Langchain, Langsmith, smolagents, or equivalent.
- Vector databases and RAG implementation patterns.
- Deploying LLM-powered applications using APIs from OpenAI, Anthropic, or open-source models.
- Strong Python programming skills.
- Excellent communication skills, with the ability to clearly explain technical concepts to diverse audiences.
It will be an added bonus if you have:
- Experience with inference frameworks and libraries (e.g., vLLM, SGLang, TensorRT-LLM, Transformers).
- Familiarity with inference optimization techniques such as quantization, batching, caching, and routing.
- Work with multimodal AI models (e.g., vision-language, speech).
- Proficiency with DevOps tools (Docker, Kubernetes).
- Contributions to open-source ML/AI projects.
Preferred tooling:
- Programming Languages– Python
- ML Frameworks and Libraries– vLLM, SGLang, TensorRT-LLM, Transformers, OpenAI/Anthropic SDKs
- Frameworks for Agentic Pipelines : Langchain / Langsmith / smolagents / equivalent
- API and Web Frameworks– FastAPI, Flask
- MLOps and DevOps tools– Kubernetes (K8s), Docker, Git
- Cloud Platforms– AWS (SageMaker, Bedrock), GCP (Vertex AI), Azure (Azure ML)
Key Employee Benefits:
- Health Insurance: 100% company-paid medical, dental, and vision coverage for employees and families.
- 401(k) Plan: Up to 4% company match with immediate vesting.
- Parental Leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers.
- Remote Work Reimbursement: Up to $85/month for mobile and internet.
- Disability & Life Insurance: Company-paid short-term, long-term, and life insurance coverage.
Compensation
We offer competitive salaries, ranging from $225k - $315k OTE (On-Target Earnings) and equity based on your experience, skills, and location.
Join Nebius Today!
Benefits & Perks:
- Competitive compensation
- Career growth and learning opportunities
- Flexibility and work-life balance
- Collaborative and innovative culture
- Opportunity to work on impactful AI projects
- International environment and talented teams
What's it like to work at Nebius:
Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI
Equal Opportunity Statement:
Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.
Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire.
If you need accommodations during the application process, please let us know.
Ready to apply?
Apply to Nebius
About Nebius:
Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.
Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.
Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.
Customer Experience:
The Customer Experience Team at Nebius AI Cloud involves tackling customers’ challenges and directly impacting their success by solving real-world AI and ML problems at massive GPU cloud scale. You’ll not only resolve issues, but play a key role in shaping clients’ business success by optimizing their AI solutions. Working with advanced GPUs such as H200, B200 and GB200, as well as modern ML frameworks, you’ll influence the development of the Nebius AI Cloud and gain experience at the intersection of infrastructure and AI. With minimal bureaucracy, you’ll have the freedom to innovate, take ownership and drive change. Opportunities for growth are abundant in this vibrant and supportive professional community.
The role
We are seeking a highly skilled and customer-focused professional to join our team as a Solutions Architect specializing in Cloud infrastructure and MLOps. As a Cloud Solutions Architect, you will play a pivotal role in designing and implementing cutting-edge solutions for our clients, leveraging cloud technologies for ML/AI teams and becoming a trusted technical advisor for building their pipelines.
You’re welcome to work remotely from the US or Canada.
Your responsibilities will include:
- Act as a trusted advisor to our clients, providing technical expertise and guidance throughout the engagement. Conduct PoC, workshops, presentations, and training sessions to educate clients on GPU cloud technologies and best practices.
- Collaborate with clients to understand their business requirements and develop solution architecture that align with their needs: design and document Infrastructure as code solutions, documentation and technical how-tos in collaboration with support engineers and technical writers.
- Help customers to optimize pipeline performance and scalability to ensure efficient utilization of cloud resources and services powered by Nebius AI.
- Act as a single point of expertise of customer scenarios for product, technical support, marketing teams.
- Assist to Marketing department efforts during events (Hackathons, conferences, workshops, webinars, etc.)
We expect you to have:
- 5 - 10 + years of experience as a cloud solutions architect, system/network engineer, developer or a similar technical role with a focus on cloud computing
- Strong hands-on experience with IaC and configuration management tools (preferably Terraform/Ansible), Kubernetes, skills of writing code in Python
- Solid understanding of GPU computing practices for ML training and inference workloads, GPU software stack components, including drivers, libraries (e.g. CUDA, OpenCL)
- Excellent communication skills
- Customer-centric mindset
It will be an added bonus if you have:
- Hands-on experience with HPC/ML orchestration frameworks (e.g. Slurm, Kubeflow)
- Hands-on experience with deep learning frameworks (e.g. TensorFlow, PyTorch)
- Solid understanding of cloud ML tools landscape from industry leaders (NVIDIA, AWS, Azure, Google)
Key Employee Benefits:
- Health Insurance: 100% company-paid medical, dental, and vision coverage for employees and families.
- 401(k) Plan: Up to 4% company match with immediate vesting.
- Parental Leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers.
- Remote Work Reimbursement: Up to $85/month for mobile and internet.
- Disability & Life Insurance: Company-paid short-term, long-term, and life insurance coverage.
Compensation
We offer competitive salaries, ranging from 225k - 315k OTE (On-Target Earnings) and equity based on your experience, skills, and location.
Join Nebius Today!
Benefits & Perks:
- Competitive compensation
- Career growth and learning opportunities
- Flexibility and work-life balance
- Collaborative and innovative culture
- Opportunity to work on impactful AI projects
- International environment and talented teams
What's it like to work at Nebius:
Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI
Equal Opportunity Statement:
Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.
Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire.
If you need accommodations during the application process, please let us know.
Ready to apply?
Apply to Nebius
About Nebius:
Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.
Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.
Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.
Summary:
Location: Remote from USA
Duration: 3 months
Start date: June 2026
Compensation: Paid
Eligibility: Current University student (Computer Science or related field), Recent Graduate or Early Career specialist
Work authorization: permitted to work in the job’s location
Why work at Nebius
Nebius is leading a new era in cloud computing to serve the global AI economy. We create the tools and resources our customers need to solve real-world challenges and transform industries, without massive infrastructure costs or the need to build large in-house AI/ML teams. Our employees work at the cutting edge of AI cloud infrastructure alongside some of the most experienced and innovative leaders and engineers in the field.
Listed on Nasdaq, Nebius has a global footprint with R&D hubs across Europe, North America, and Israel. The team of over 1400+ employees includes more than 400 highly skilled engineers with deep expertise across hardware and software engineering, as well as an in-house AI R&D team.
The role
Customer experience at Nebius AI Cloud focuses on helping customers successfully adopt and scale AI workloads. As an intern, you’ll support this mission by learning how real-world AI systems are designed, deployed, and optimized at GPU cloud scale. You’ll gain exposure to modern ML frameworks, large-scale GPU infrastructure (including NVIDIA Hopper, Blackwell and Grace Blackwell platforms), and the collaboration between customers, engineering, and product teams.
This role offers a strong learning environment with mentorship, minimal bureaucracy, and opportunities to develop both technical and communication skills.
We are looking for an AI/ML Solutions Architect Intern to support AI-focused customers using Nebius services. This is a learning-focused role designed for students or early-career candidates who are interested in AI infrastructure, cloud platforms, and applied machine learning.
You will work closely with experienced Solutions Architects, Engineers, and Product teams to help design, document, and support AI solutions.
Your responsibilities will include:
- Assist in designing and documenting AI and ML solutions.
- Learn how distributed training and inference workloads run on multi-GPU cloud-based systems.
- Help prepare technical materials such as presentations, documentation, tutorials, or demos.
- Participate in investigation, troubleshooting and optimization tasks under guidance from senior team members.
We expect you to have:
- Currently pursuing or recently completed a degree in Computer Science, Engineering, Data Science, or a related field.
- Solid understanding of machine learning concepts and workflows.
- Familiarity with at least one ML framework such as PyTorch, TensorFlow, or JAX.
- Comfort with programming in Python (other languages are a plus).
- Interest in cloud infrastructure, GPUs, and large-scale AI systems.
- Strong communication skills and a willingness to learn and ask questions.
Nice to have:
- Exposure to Kubernetes, Docker, or other container technologies.
- Familiarity with Git or basic DevOps workflows.
- Coursework or projects involving distributed systems, MLOps, or deep learning.
- Experience with AI projects from school, hackathons, or personal work.
Tools you may learn and use:
- Programming: Python (plus exposure to Go, Java, or C++).
- ML Frameworks: PyTorch, TensorFlow, JAX, Hugging Face.
- Infrastructure & DevOps: Docker, Git, Kubernetes, Terraform.
- Schedulers & Orchestration: Kubernetes, Slurm (learning-focused).
What we offer
- Competitive salary (ranging from 8,160 – 12,240 USD) and comprehensive benefits package.
- Mentorship from experienced AI, ML, and cloud infrastructure professionals.
- Hands-on experience with real customer workloads and production systems.
- Remote work flexibility and a collaborative, supportive team environment.
- Opportunity to be considered for a full-time role after the Program.
We’re growing and expanding our products every day. If you’re up to the challenge and are excited about AI and ML as much as we are, join us!
Benefits & Perks:
- Competitive compensation
- Career growth and learning opportunities
- Flexibility and work-life balance
- Collaborative and innovative culture
- Opportunity to work on impactful AI projects
- International environment and talented teams
What's it like to work at Nebius:
Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI
Equal Opportunity Statement:
Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.
Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire.
If you need accommodations during the application process, please let us know.
Ready to apply?
Apply to Nebius
About Nebius:
Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.
Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.
Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.
The role
We are building a high-performance AI inference platform for developer-native teams running latency- and cost-sensitive workloads at scale.
In AI infrastructure, PoC success does not always guarantee production success. This role exists to ensure that what we commit to with customers is scalable, efficient, and aligned with platform strategy.
We are looking for a Presales Architect to become a foundational technical partner to our customers and a force multiplier for Sales and Engineering. You will shape complex AI workloads from first discovery through production feasibility validation, ensuring technical rigor, economic viability, and scalable architecture decisions.
You will operate at the intersection of customer ambition, engineering reality, and commercial growth, influencing:
- Revenue quality
- Engineering focus
- Product evolution
- Customer trust at scale
You’re welcome to work remotely from the United States.
Your responsibilities will include:
Strategic Technical Discovery
- Lead deep technical discovery with engineering teams and technical founders
- Understand model requirements, traffic expectations, latency constraints, GPU economics, and system dependencies
- Translate customer ambition into production-feasible architecture.
- Identify hidden technical risks early
Commercial Acceleration
- Partner tightly with Sales on strategic deals
- Influence deal strategy through architectural clarity
- Prevent misaligned commitments before engineering allocation
- Increase PoC-to-production conversion by ensuring technical realism
PoC Architecture & Validation
- Define measurable success criteria (latency, TTFT, throughput, cost envelope)
- Classify workload complexity and required optimization depth
- Align appropriate resources (ML Solution Architects, engineering, GPU capacity, etc.)
- Drive structured Go / No-Go decisions
- Prevent uncontrolled customization or hidden R&D
Pattern Recognition & Platform Leverage
- Identify recurring configuration patterns across customers
- Quantify demand for advanced optimizations (quantization, speculative decoding, etc.)
- Surface structured insights to Product and Engineering
- Help evolve platform capabilities based on real workload data
We expect you to have:
- Deep understanding of AI inference systems and GPU-backed infrastructure
- Experience with LLM workloads and performance-sensitive environments
- Experience with inference frameworks and libraries (e.g., vLLM, SGLang, TensorRT-LLM).
- Ability to reason about latency, throughput, cost, and architecture tradeoffs
- Strong customer presence with engineering-first organizations
- Comfort challenging assumptions and pushing back constructively
- Commercial awareness – you understand that engineering time is a strategic resource
Preferred Technical Stack
- Programming Languages– Python
- Frameworks and Libraries– vLLM, SGLang, TensorRT-LLM, OpenAI/Anthropic SDKs
- Frameworks for Agentic Pipelines : Langchain / Langsmith / smolagents / equivalent
- API and Web Frameworks– FastAPI, Flask
- MLOps and DevOps tools– Kubernetes (K8s), Docker, Git
- Cloud Platforms– AWS (SageMaker, Bedrock), GCP (Vertex AI), Azure (Azure ML)
What Success Looks Like
- Strategic deals are technically sound before engineering engagement
- PoCs are clearly scoped and economically justified
- Engineering capacity is allocated predictably
- Conversion to production improves
- Customers view you as a trusted architectural advisor
Key employee benefits in the US:
- Health insurance: 100% company-paid medical, dental, and vision coverage for employees and families.
- 401(k) plan: Up to 4% company match with immediate vesting.
- Parental leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers.
- Remote work reimbursement: Up to $85/month for mobile and internet.
- Disability & life insurance: Company-paid short-term, long-term and life insurance coverage.
Compensation
We offer competitive salaries, ranging from $152k - 228k base + RSU's and performance bonus's.
Benefits & Perks:
- Competitive compensation
- Career growth and learning opportunities
- Flexibility and work-life balance
- Collaborative and innovative culture
- Opportunity to work on impactful AI projects
- International environment and talented teams
What's it like to work at Nebius:
Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI
Equal Opportunity Statement:
Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.
Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire.
If you need accommodations during the application process, please let us know.
Ready to apply?
Apply to Nebius
About Nebius:
Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.
Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.
Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.
Customer experience:
Customer experience at Nebius AI Cloud involves tackling customers’ challenges and directly impacting their success by solving real-world AI and ML problems at massive GPU cloud scale. You’ll not only resolve issues, but play a key role in shaping clients’ business success by optimizing their AI solutions. Working with advanced GPUs such as H200, B200 and GB200, as well as modern ML frameworks, you’ll influence the development of the Nebius AI Cloud and gain experience at the intersection of infrastructure and AI. With minimal bureaucracy, you’ll have the freedom to innovate, take ownership and drive change. Opportunities for growth are abundant in this vibrant and supportive professional community.
The role
We are looking for a Partner Solutions Architect to serve as the technical interface between Nebius and our strategic technology partners, ranging from data platforms and MLOps vendors to AI frameworks and ISVs that build on GPU infrastructure.
This is a hands-on engineering and integration role. You will design and develop integrated solutions, build reference implementations, enable partner engineering teams, and ensure joint customers succeed with combined offerings. You will influence Nebius’ product roadmap and drive deep technical collaboration across partner ecosystems.
You’re welcome to work remotely from the United States or Canada.
Your responsibilities will include:
- Own the technical relationship with strategic partners as the primary interface to Nebius engineering and product
- Design and architect high-impact integration solutions, delivering clear joint customer value
- Build and maintain reference implementations and production-grade integrations
- Define enterprise-ready integration patterns (networking, security, compliance, observability)
- Translate partner and customer feedback into actionable product and roadmap requirements
- Enable partner teams through technical documentation, training, and demo environments
- Provide technical leadership in joint customer deployments, architecture reviews, and complex troubleshooting
We expect you to have:
- 7+ years in solutions architecture, partner engineering, or technical pre-sales at cloud or data platform companies
- Strong expertise in cloud infrastructure
- Hands-on experience with GPU-accelerated AI/ML workflows (training, inference, MLOps)
- Proven background in integration architecture (API design, data pipelines, security, observability)
- Experience with Python and IaC tools
- Excellent communication skills with the ability to engage technical and non-technical stakeholders
It will be an added bonus if you have:
- Track record of building or scaling partner technical programs or ecosystems
- Experience working with or at Snowflake, Databricks, AWS, Azure, or GCP
- Background in ML lifecycle (training pipelines, fine-tuning, inference optimization, RAG
- Understanding of compliance standards: SOC 2, HIPAA, GDPR, FedRAMP
Key Employee Benefits:
- Health Insurance: 100% company-paid medical, dental, and vision coverage for employees and families.
- 401(k) Plan: Up to 4% company match with immediate vesting.
- Parental Leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers.
- Remote Work Reimbursement: Up to $85/month for mobile and internet.
- Disability & Life Insurance: Company-paid short-term, long-term, and life insurance coverage.
Compensation
We offer competitive salaries, ranging from 225k - 315k OTE (On-Target Earnings) and equity based on your experience, skills, and location.
Join Nebius Today!
Benefits & Perks:
- Competitive compensation
- Career growth and learning opportunities
- Flexibility and work-life balance
- Collaborative and innovative culture
- Opportunity to work on impactful AI projects
- International environment and talented teams
What's it like to work at Nebius:
Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI
Equal Opportunity Statement:
Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.
Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire.
If you need accommodations during the application process, please let us know.
Ready to apply?
Apply to Nebius
AI/ML Specialist Solutions Architect
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About Nebius:
Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.
Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.
Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.
Customer Experience:
The Customer Experience Team at Nebius AI Cloud involves tackling customers’ challenges and directly impacting their success by solving real-world AI and ML problems at massive GPU cloud scale. You’ll not only resolve issues, but play a key role in shaping clients’ business success by optimizing their AI solutions. Working with advanced GPUs such as H200, B200 and GB200, as well as modern ML frameworks, you’ll influence the development of the Nebius AI Cloud and gain experience at the intersection of infrastructure and AI. With minimal bureaucracy, you’ll have the freedom to innovate, take ownership and drive change. Opportunities for growth are abundant in this vibrant and supportive professional community.
The role
We are seeking a highly skilled and customer-focused professional to join our team as a AI/ML Specialist Solutions Architect specializing in Cloud infrastructure and MLOps. As a Cloud Solutions Architect, you will play a pivotal role in designing and implementing cutting-edge solutions for our clients, leveraging cloud technologies for ML/AI teams and becoming a trusted technical advisor for building their pipelines.
You’re welcome to work remotely from the US or Canada.
Your responsibilities will include:
- Act as a trusted advisor to our clients, providing technical expertise and guidance throughout the engagement. Conduct PoC, workshops, presentations, and training sessions to educate clients on GPU cloud technologies and best practices.
- Collaborate with clients to understand their business requirements and develop solution architecture that align with their needs: design and document Infrastructure as code solutions, documentation and technical how-tos in collaboration with support engineers and technical writers.
- Help customers to optimize pipeline performance and scalability to ensure efficient utilization of cloud resources and services powered by Nebius AI.
- Act as a single point of expertise of customer scenarios for product, technical support, marketing teams.
- Assist to Marketing department efforts during events (Hackathons, conferences, workshops, webinars, etc.)
We expect you to have:
- 5 - 10 + years of experience as a cloud solutions architect, system/network engineer, developer or a similar technical role with a focus on cloud computing
- Strong hands-on experience with IaC and configuration management tools (preferably Terraform/Ansible), Kubernetes, skills of writing code in Python
- Solid understanding of GPU computing practices for ML training and inference workloads, GPU software stack components, including drivers, libraries (e.g. CUDA, OpenCL)
- Excellent communication skills
- Customer-centric mindset
It will be an added bonus if you have:
- Hands-on experience with HPC/ML orchestration frameworks (e.g. Slurm, Kubeflow)
- Hands-on experience with deep learning frameworks (e.g. TensorFlow, PyTorch)
- Solid understanding of cloud ML tools landscape from industry leaders (NVIDIA, AWS, Azure, Google)
Key Employee Benefits:
- Health Insurance: 100% company-paid medical, dental, and vision coverage for employees and families.
- 401(k) Plan: Up to 4% company match with immediate vesting.
- Parental Leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers.
- Remote Work Reimbursement: Up to $85/month for mobile and internet.
- Disability & Life Insurance: Company-paid short-term, long-term, and life insurance coverage.
Compensation
We offer competitive salaries, ranging from 225k - 315k OTE (On-Target Earnings) and equity based on your experience, skills, and location.
Join Nebius Today!
Benefits & Perks:
- Competitive compensation
- Career growth and learning opportunities
- Flexibility and work-life balance
- Collaborative and innovative culture
- Opportunity to work on impactful AI projects
- International environment and talented teams
What's it like to work at Nebius:
Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI
Equal Opportunity Statement:
Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.
Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire.
If you need accommodations during the application process, please let us know.
Ready to apply?
Apply to Nebius
Senior Applied AI Solutions Engineer
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About Nebius:
Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.
Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.
Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.
This role sits at the intersection of deep ML engineering and product impact. You'll spend roughly half your time in the field — helping new customers move from POC to production, running technical onboarding, and working hands-on through their ML stack. The other half you'll spend building — prototyping applied AI use cases that show what's possible on the platform, going deep on emerging techniques before they're mainstream, and turning that expertise into concrete product direction.
This is not a presales role. You get your hands dirty every day.
What success looks like in 12 months
- The product and sales teams have a library of working, polished demos they reach for on calls
- Enterprise customers you've touched have meaningfully faster time-to-value than those you haven't
- At least 2–3 product changes were shipped because of feedback you originated
- The team understands where applied AI is heading 6–12 months from now, partly because you told them
- Build prototypes and demos across the product portfolio — serverless inference, databases, MLflow, MLOps, and vertical use cases in Physical AI and HCLS — that become assets for sales, product, and engineering teams
- Support new customers hands-on through POC design, technical onboarding, and validation; act as the bridge between their ML team and the platform during the critical first months
- Go deep on emerging applied AI — new training techniques, inference optimizations, agentic architectures, new frameworks — and turn findings into working prototypes, writeups, and product recommendations
- Feed the product roadmap with specific, grounded feedback; be the voice of "here's what broke in three customer POCs last month and here's what needs to change"
- Develop reusable technical assets — notebooks, reference architectures, benchmark results — that reduce onboarding friction at scale
- You've fine-tuned large models, debugged distributed training jobs, built production RAG or agentic pipelines, and optimized inference on GPU infrastructure — not just read about it
- You're fluent in the modern ML stack: PyTorch, HuggingFace, CUDA fundamentals, Kubernetes for ML, MLflow or equivalent, vector databases
- You've worked with enterprise ML teams — whether as a solutions engineer, customer engineer, or an ML engineer who collaborated closely with customers
- You read papers and implement them — not for credit, but because it's how you stay sharp
- You communicate with calibration: you can explain activation checkpointing tradeoffs to an ML engineer in the morning and the cost implication to a CTO in the afternoon
- Experience in any of our vertical domains: Physical AI / robotics / simulation, HCLS (drug discovery, medical imaging, clinical NLP), or enterprise AI application development
- Familiarity with MLOps at scale (Kubeflow, Metaflow, Argo, Ray)
- Prior work at a cloud provider or AI infrastructure company
- You've shared technical work publicly — notebooks, talks, blog posts that people actually use
- Competitive salary and comprehensive benefits package.
- Opportunities for professional growth within Nebius.
- Flexible working arrangements.
- A dynamic and collaborative work environment that values initiative and innovation.
Compensation
We offer competitive compensation packages based on experience.
Benefits & Perks:
- Competitive compensation
- Career growth and learning opportunities
- Flexibility and work-life balance
- Collaborative and innovative culture
- Opportunity to work on impactful AI projects
- International environment and talented teams
What's it like to work at Nebius:
Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI
Equal Opportunity Statement:
Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.
Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire.
If you need accommodations during the application process, please let us know.
Ready to apply?
Apply to Nebius
Director of Platform Engineering
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The climate crisis is the defining challenge of our time—but it’s also the greatest opportunity for innovation, and a challenge we’re proud to take on. At Overstory, we’re harnessing cutting-edge technology to enable a resilient electrical grid that keeps communities thriving as our world changes.
The grid is the backbone of life as we know it. It powers hospitals, keeps food fresh, and ensures communities stay connected. But extreme weather, aging infrastructure, and growing wildfire risks are putting this critical system under pressure. All of this combined makes the electric utility industry the greatest opportunity for tackling climate change.
One of the leading causes of catastrophic wildfires and power outages? Trees and brush coming into contact with power lines.
That’s where we help. At Overstory, we use AI and advanced satellite imagery to pinpoint and prioritize vegetation risks before they materialize. By giving utilities critical analysis on those risks, we’re helping prevent outages, reduce wildfire risks, and accelerate the transition to a safer, more resilient grid.
Our team spans the Americas and Europe, and we work with utility partners across the Americas and beyond. We’re outdoor enthusiasts, musicians, artists, athletes, parents, and adventurers. What unites us is a passion for solving complex problems, a commitment to climate action, and the belief that technology should be a force for good.
Join us to help us build a more resilient world together.
Role & Team
We’re looking for a Director of Platform & Infrastructure to own and evolve our core engineering foundations. Reporting to our VP of Product Engineering, this role will lead SRE, MLOps, and Platform teams with a mandate to create leverage across the entire organization.
As a scaling startup, we’re evolving from early-stage infrastructure to a more mature, reliable platform that can support rapid product development and growing customer demand. This role is critical in helping us make that transition — building systems, standards, and teams that enable speed today while laying the foundation for long-term scale.
Partnering closely with product, data, and application engineering teams, you will set the technical vision, define best practices, and ensure our infrastructure enables teams to move fast with confidence.
This is a highly cross-functional leadership role for someone who combines deep technical judgment with a systems mindset, strong people leadership, and a passion for building platforms that empower others.
Time zone requirement: Europe (GMT/WET, CET, EET) and Eastern North America (NST, AST, EST)
What You'll Do
- Own the platform strategy across Platform, MLOps, and SRE, aligning it with company and product goals
- Grow senior ICs (and eventually manages) across multiple teams, fostering strong technical leadership and healthy team cultures
- Define and evolve our platform vision, including developer experience, internal tooling, CI/CD, infrastructure, observability, and reliability standards
- Oversee MLOps systems that support model development, training, deployment, monitoring, and governance in production
- Partner cross-functionally with Product, ML, Data, Security, and Compliance to ensure the platform meets current and future needs
- Balance speed and stability, making thoughtful tradeoffs between innovation, cost, reliability, and operational excellence
- Set metrics and accountability for platform performance, reliability, and developer productivity
Skills & Experience
- 10+ years experience leading platform, infrastructure, or reliability teams in a scaling startup environment, including navigating ambiguity, rapid growth, and the transition from early-stage systems to more mature, repeatable platforms
- Strong understanding of cloud-native infrastructure (GCP strongly preferred), Kubernetes, CI/CD, and modern DevOps practices
- Experience supporting machine learning systems in production, including model deployment, monitoring, and lifecycle management
- A track record of building reliable, scalable systems used by fast-moving product teams
- Excellent people leadership skills — you know how to coach managers, grow talent, and build inclusive, high-performing teams
- Strong communication skills and the ability to influence across org boundaries
- Experience in data- or ML-heavy products
Nice To Have
- Experience with geospatial data, image processing or mapping technology
Note: We believe that all people are capable of great things. We encourage you to apply even if you do not meet all of the requirements that are listed within this job description.
What We Offer
- Competitive, location-specific compensation and benefits.
- Flexible, autonomous and collaborative working environment rooted in trust - we build our work days around our lives, not the other way around
- Home office stipend, coworking and ongoing education budgets
- A company culture that genuinely embodies each of our core values
- To be part of truly mission-driven work that reduces wildfires, protects earth’s natural resources and helps solve our climate crisis
About Our Team
We are a group of 100 people from all over the world. Fifteen nationalities are represented in our team and at last count we speak fourteen languages: English, Dutch, French, Spanish, German, Italian, Portuguese, Russian, Luxembourgish, Lithuanian, Bulgarian, Cantonese, Estonian, and Danish.
We work remotely from eleven countries and are looking for candidates that are living and working in one of them: United States, the Netherlands, United Kingdom, Ireland, Estonia, Portugal, France, Sweden, Switzerland, Denmark and Canada. We gather once a year in-person for our unforgettable team gathering event. We also offer the option to occasionally meet up for in-person collaboration.
Diversity & Inclusion
The climate crisis is a human crisis that requires diverse perspectives to solve.
We place enormous value on diversity and believe that the best ideas emerge when people with different backgrounds and experience work together. We remain committed to scaling a team that reflects the communities we serve, and strive to uphold equitable and inclusive practices across every aspect of our business. We are responsible for creating and maintaining a culture where everyone - regardless of background - has a voice in building a sustainable future.
Our Values
Tackling the climate crisis is our greatest mission.
We act with urgency.
Our curiosity fuels our growth.
We recognize that change is constant, and we find joy and power in exploration.
We’re rooted in diversity.
Just as ecosystems need biodiversity to thrive, our resiliency comes from our differences.
We care for each other.
We love the power of machines but we nurture each other as humans.
Trust is fundamental.
We assume the best in everyone, and we share ideas openly so that we have a positive impact.
_________________________________
Use of AI in Our Hiring Process
We sometimes use AI tools to support parts of our hiring process, such as helping us manage applications more efficiently or ensuring job descriptions are clear and inclusive. All hiring decisions are always made by people, not machines. Any data processed by AI is handled securely in line with GDPR and our Privacy Notice.
Ready to apply?
Apply to Overstory
Staff Machine Learning Engineer - Wildfire
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The climate crisis is the defining challenge of our time—but it’s also the greatest opportunity for innovation, and a challenge we’re proud to take on. At Overstory, we’re harnessing cutting-edge technology to enable a resilient electrical grid that keeps communities thriving as our world changes.
The grid is the backbone of life as we know it. It powers hospitals, keeps food fresh, and ensures communities stay connected. But extreme weather, aging infrastructure, and growing wildfire risks are putting this critical system under pressure. All of this combined makes the electric utility industry the greatest opportunity for tackling climate change.
One of the leading causes of catastrophic wildfires and power outages? Trees and brush coming into contact with power lines.
That’s where we help. At Overstory, we use AI and advanced satellite imagery to pinpoint and prioritize vegetation risks before they materialize. By giving utilities critical analysis on those risks, we’re helping prevent outages, reduce wildfire risks, and accelerate the transition to a safer, more resilient grid.
Our team spans the Americas and Europe, and we work with utility partners across the Americas and beyond. We’re outdoor enthusiasts, musicians, artists, athletes, parents, and adventurers. What unites us is a passion for solving complex problems, a commitment to climate action, and the belief that technology should be a force for good.
Join us to help us build a more resilient world together.
Role & Team
As a Staff Machine Learning Engineer at Overstory, you will lead the development and scaling of our Wildfire Fuel Detection Model. This core engine powers how we understand vegetation structure, fuel loads, and wildfire risk from satellite and environmental data. You’ll help shape the next generation of Overstory’s modeling capabilities by combining cutting-edge ML techniques, large-scale geospatial data, and real-world domain expertise.
Reporting to our VP of Product Engineering, you’ll work closely with data scientists, ML engineers, and product teams to ensure our wildfire models are accurate, robust, and production-ready – balancing scientific rigor with practical engineering excellence. As a senior technical leader, you’ll mentor other engineers, drive architectural decisions, and define standards for modeling, experimentation, and deployment across Overstory.
Time zone requirement: Eastern North America (NST, AST, EST)
What You’ll Do
In collaboration with data, ML, and science colleagues, you will:
- Architect and build advanced ML models to map and predict vegetation and fuel conditions across diverse geographies.
- Design and maintain robust data and feature pipelines for large-scale geospatial and temporal data.
- Partner with wildfire science and product teams to define modeling objectives and evaluation metrics tied to real-world impact.
- Build reproducible experimentation frameworks and model evaluation workflows.
- Scale models from research to production with a focus on performance, reliability, and explainability.
- Lead the evolution of ML systems, tooling, and processes — ensuring that our wildfire fuelscape models remain state-of-the-art and maintainable.
- Collaborate with MLOps peers to streamline training, inference, and monitoring in production environments.
Skills & Experience
- Experience thriving at the intersection of machine learning, geospatial data, and environmental science; deeply motivated by the opportunity to reduce wildfire risk through data-driven insights
- 10+ years of experience designing and building production-grade ML pipelines and systems
- Strong background in deep learning, computer vision, or remote sensing
- Skilled in designing end-to-end ML systems — from data ingestion and preprocessing to deployment and monitoring
- Hands-on experience with frameworks like PyTorch, TensorFlow, XGBoost, or LightGBM, and data tools like Dask, Spark, or GeoPandas
- Familiarity with GCP and Vertex AI, or similar cloud-based ML platforms
- Strong communication skills and ability to collaborate across technical and scientific domains
- Comfortable leading architectural discussions and mentoring other engineers
Nice To Have
- Background in wildfire science, forestry, or remote sensing
- Experience integrating physics-based models with ML or working with active learning and uncertainty quantification
- Experience in model interpretability and data provenance for environmental ML systems
- Experience with deep learning models for weather or climate data
- Experience in remote-first or globally distributed teams
Note: We believe that all people are capable of great things. We encourage you to apply even if you do not meet all of the requirements that are listed within this job description.
What We Offer
- Competitive, location-specific compensation and benefits
- Flexible, autonomous and collaborative working environment rooted in trust - we build our work days around our lives, not the other way around
- Home office stipend, coworking and ongoing education budgets
- A company culture that genuinely embodies each of our core values
- To be part of truly mission-driven work that reduces wildfires, protects earth’s natural resources and helps solve our climate crisis
About Our Team
We are a group of 100 people from all over the world. Fifteen nationalities are represented in our team and at last count we speak fourteen languages: English, Dutch, French, Spanish, German, Italian, Portuguese, Russian, Luxembourgish, Lithuanian, Bulgarian, Cantonese, Estonian, and Danish.
We work remotely from eleven countries and are looking for candidates that are living and working in one of them: United States, the Netherlands, United Kingdom, Ireland, Estonia, Portugal, France, Sweden, Switzerland, Denmark and Canada. We gather once a year in-person for our unforgettable team gathering event. We also offer the option to occasionally meet up for in-person collaboration.
Diversity & Inclusion
The climate crisis is a human crisis that requires diverse perspectives to solve.
We place enormous value on diversity and believe that the best ideas emerge when people with different backgrounds and experience work together. We remain committed to scaling a team that reflects the communities we serve, and strive to uphold equitable and inclusive practices across every aspect of our business. We are responsible for creating and maintaining a culture where everyone - regardless of background - has a voice in building a sustainable future.
Our Values
Tackling the climate crisis is our greatest mission.
We act with urgency.
Our curiosity fuels our growth.
We recognize that change is constant, and we find joy and power in exploration.
We’re rooted in diversity.
Just as ecosystems need biodiversity to thrive, our resiliency comes from our differences.
We care for each other.
We love the power of machines but we nurture each other as humans.
Trust is fundamental.
We assume the best in everyone, and we share ideas openly so that we have a positive impact.
_________________________________
Use of AI in Our Hiring Process
We sometimes use AI tools to support parts of our hiring process, such as helping us manage applications more efficiently or ensuring job descriptions are clear and inclusive. All hiring decisions are always made by people, not machines. Any data processed by AI is handled securely in line with GDPR and our Privacy Notice.
Ready to apply?
Apply to Overstory
Staff Backend Engineer, Customer Value Optimisation
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The Role
We're looking for a Staff Backend Engineer to join our Customer Value Optimization (CVO) tribe at HelloFresh. This is a high-impact individual contributor role sitting at the intersection of Data Science and Backend Engineering — you'll be the technical bridge that turns ML models into reliable, scalable production systems.
You'll work across squads within the CVO tribe, partnering closely with Data Scientists and Backend Engineers to define how we serve ML models at scale, raise the technical bar, and accelerate the tribe's ability to deliver value to our customers.
What you’ll do
- Design, build, and own robust, scalable infrastructure for live serving of ML models in production
- Act as the technical bridge between Data Science and Backend Engineering teams within the CVO tribe — translating DS needs into scalable engineering solutions
- Define and drive best practices for model serving, APIs, and system design across squads
- Lead cross-squad technical initiatives, from architecture decisions to hands-on implementation
- Partner with Data Scientists to ensure models are production-ready — performant, observable, and maintainable
- Contribute to tribe-wide engineering standards and shape the technical roadmap
- Mentor and support engineers across squads without direct line management responsibility
What you’ll bring
- 7+ years of backend engineering experience, with a strong foundation in Python
- Proven experience building and operating ML model serving systems or ML platforms in production
- Deep understanding of distributed systems, APIs, and microservices architecture
- Strong track record of working across team boundaries to deliver complex, cross-functional projects
- Excellent communication skills — able to work fluently with Data Scientists, Machine Learning Engineers, and Data Engineers
- A collaborative, low-ego approach with strong technical judgment
Nice to Have
- Experience with ML frameworks and serving tools
- Familiarity with feature stores, model registries, or MLOps tooling
- Background in e-commerce, subscription, or personalization domains
Ready to apply?
Apply to HelloFresh
Specialist Solutions Architect - AI/ML
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P-226
As a Specialist Solutions Architect (SSA) - AI/ML Engineering, you will be the trusted technical ML & AI expert to both Databricks customers and the Field Engineering organization. You will work with Solution Architects to guide customers in architecting production-grade ML & AI applications on Databricks, while aligning their technical roadmap with the continually evolving Databricks Data Intelligence Platform. You will continue to strengthen your technical skills through applying cutting-edge technologies in GenAI, MLOps, and ML more broadly, expanding your impact through mentorship, and establishing yourself as an AI thought leader.
The impact you will have:
- Architect production-level ML & AI workloads for customers using our unified platform, including agents, end-to-end ML pipelines, training/inference optimization, integration with cloud-native services, MLOps, etc.
- Serve as a trusted practitioner for enterprise GenAI solutions, including RAG architectures, agentic systems (tool-calling agents, multi-agent orchestration, guardrails), natural language querying of structured data, AI evaluation and observability, and monitoring systems
- Build, scale, and optimize customer AI workloads and apply best-in-class MLOps to productionize these workloads across a variety of domains
- Provide advanced technical support to Solution Architects during the technical sale, ranging from feature engineering, training, tracking, serving, to model monitoring, all within a single platform, as well as participating in the larger ML SME community in Databricks
- Collaborate cross-functionally with the product and engineering teams to represent the voice of the customer, define priorities, and influence the product roadmap, helping with the adoption of Databricks’ AI offerings
What we look for:
- 5+ years of hands-on industry ML experience in at least one of the following:
- ML Engineer: Build and maintain production-grade cloud (AWS/Azure/GCP) infrastructure that supports the deployment of ML applications, including drift monitoring.
- AI Engineer: Experience with the latest techniques in LLMs & agentic systems, including vector databases, fine-tuning LLMs, AI guardrail systems, and deploying LLMs with tools such as HuggingFace, Langchain, and OpenAI
- Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience
- Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike
- Passion for collaboration, life-long learning, and driving business value through ML & AI
- [Preferred] 2+ years customer-facing experience in a pre-sales or post-sales role
- Can meet expectations for technical training and role-specific outcomes within 3 months of hire
- This role can be remote, but we prefer that you be located in the job listing area and can travel up to 30% when needed
Pay Range Transparency
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.
About Databricks
Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Ready to apply?
Apply to Databricks
DevOps Engineer - Senior Vice President
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About the Role
The Platform Infrastructure team at iCapital plays a critical role in ensuring that both production and development environments operate smoothly, securely, and reliably. This role leverages advanced cloud capabilities to support the Platform Infrastructure strategy of market agility and lean operating principles, with a strong emphasis on quality to meet the ever‑growing demands of our clients.
We are seeking highly collaborative, creative, and intellectually curious MLOps/DevOps Engineers with deep expertise in machine learning operations, cloud infrastructure, CI/CD automation, Kubernetes, and security. This role requires hands‑on experience designing, building, and operating scalable DevOps and enterprise‑grade MLOps platforms, including model lifecycle automation, observability, and governance.
As a Platform Engineer, you will wear multiple hats in a highly visible role, partnering closely with engineering, security, data, and business teams to deliver secure, reliable, and highly automated platforms that support both application and machine‑learning workloads.
Responsibilities
- Design, build, and operate MLOps pipelines supporting the full ML lifecycle (training, validation, deployment, monitoring).
- Enable production workloads for AI/ML and Generative AI systems, including LLM‑based services.
- Develop and maintain CI/CD pipelines for AI/ML services and supporting infrastructure.
- Build and manage cloud‑native infrastructure on AWS, with heavy use of Kubernetes and containerized workloads.
- Automate infrastructure provisioning and configuration using Infrastructure as Code (Terraform).
- Implement model versioning, experiment tracking, and artifact management across environments.
- Ensure reliability, scalability, observability, and cost efficiency of AI platforms.
- Partner with AI/ML engineers to operationalize models and standardize deployment patterns.
- Implement monitoring and alerting for system health, model performance, and drift.
- Enforce security, compliance, and governance requirements for AI workloads.
- Participate in incident response, root cause analysis, and continuous improvement initiatives.
- Document standards, best practices, and reference architectures for MLOps and AI infrastructure.
Required Qualifications
- 15+ years of experience in DevOps, SRE, or Platform Engineering, with AWS as a primary cloud.
- Experience supporting machine learning systems in production, including deployment and monitoring concerns.
- Hands‑on experience with machine learning platforms, particularly AWS SageMaker (required).
- Strong hands-on experience with Kubernetes, containerized workloads, and cloud networking.
- Proven experience building and operating CI/CD pipelines (e.g., GitLab CI, ArgoCD).
- Strong proficiency with Terraform and scripting/programming in Python or similar languages.
- Solid Linux, systems, and troubleshooting fundamentals.
- Excellent communication skills and ability to work across teams.
- Direct experience with MLOps platforms and tooling (model registries, experiment tracking, feature stores).
- Exposure to Generative AI / LLM workloads in production environments.
- Familiarity with data stores commonly used in ML systems (e.g., Postgres, DynamoDB, object storage).
- Experience operating in regulated or fintech environments.
- Background in cost optimization for compute‑intensive workloads.
- Strong written and verbal communication skills.
- AWS certifications are a plus.
Benefits
The base salary range for this role is $180,000 to $230,000 depending on experience. iCapital offers a compensation package which includes salary, equity for all full-time employees, and an annual performance bonus. Employees also receive a comprehensive benefits package that includes an employer matched retirement plan, generously subsidized healthcare with 100% employer paid dental, vision, telemedicine, and virtual mental health counseling, parental leave, and unlimited paid time off (PTO).
We believe the best ideas and innovation happen when we are together. Employees in this role will work in the office Monday-Thursday, with the flexibility to work remotely on Friday.
For additional information on iCapital, please visit https://www.icapitalnetwork.com/about-us Twitter: @icapitalnetwork | LinkedIn: https://www.linkedin.com/company/icapital-network-inc | Awards Disclaimer: https://www.icapitalnetwork.com/about-us/recognition/
iCapital is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, gender, sexual orientation, gender identity, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics
Ready to apply?
Apply to iCapital
AI Solution Lead-Generative AI & Large Language Models
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Orion Innovation is a premier, award-winning, global business and technology services firm. Orion delivers game-changing business transformation and product development rooted in digital strategy, experience design, and engineering, with a unique combination of agility, scale, and maturity. We work with a wide range of clients across many industries including financial services, professional services, telecommunications and media, consumer products, automotive, industrial automation, professional sports and entertainment, life sciences, ecommerce, and education.
The AI Solution Lead will work closely with engineering teams and client stakeholders to translate cutting-edge AI capabilities into reliable production systems, while ensuring governance, transparency, and responsible AI practices.
The ideal candidate combines technical depth, research awareness, and strong communication skills, enabling them to represent our company confidently in front of senior client stakeholders.
Key Responsibilities
AI Solution & Design
- Design and deliver enterprise-grade AI solutions leveraging Generative AI and Large Language Models.
- Define designs for LLM-based systems, agentic workflows, retrieval-augmented generation (RAG), and AI copilots.
- Evaluate and select appropriate models, frameworks, and infrastructure for production AI systems.
- Ensure scalability, reliability, and performance of deployed AI solutions.
Machine Learning & Model Expertise
- Provide deep technical expertise in:
- Large Language Models (LLMs)
- Transformer architectures
- Generative AI techniques
- Model evaluation and benchmarking
- Design approaches for fine-tuning, prompt engineering, and model adaptation.
- Guide teams on best practices in ML pipelines, experimentation, and model lifecycle management.
Production Deployment & MLOps
- Lead deployment of machine learning and GenAI systems into production environments.
- Architect and implement MLOps pipelines, model monitoring, and continuous improvement processes.
- Ensure AI systems are secure, scalable, and operationally maintainable.
AI Governance & Responsible AI
- Implement frameworks for:
- AI governance
- Model explainability
- Transparency
- Risk management
- Ensure compliance with enterprise AI governance standards and regulatory expectations.
- Define policies for model validation, bias mitigation, and responsible deployment.
Client Engagement & Technical Leadership
- Act as a trusted technical advisor to client stakeholders.
- Clearly communicate complex AI concepts to executives, architects, and engineering teams.
- Represent the company with credibility in technical and strategic discussions around AI adoption.
- Work closely with client teams to translate business problems into AI-driven solutions.
Research & Innovation
- Stay current with emerging developments in:
- Generative AI
- Large language models
- AI agents and agentic architectures
- AI infrastructure and tooling
- Evaluate new research and technologies to determine their practical applicability in enterprise environments.
- Help shape the organization’s AI strategy and technical direction.
Required Qualifications
- Master’s degree in Data Science, Machine Learning, Computer Science, or related field.
- Strong expertise in machine learning fundamentals and modern generative AI technologies.
- Proven experience designing and deploying AI/ML systems in production environments.
- Deep knowledge of:
- Large Language Models
- Generative AI architectures
- ML pipelines and model lifecycle management
- Experience working with AI frameworks and ecosystems used for building GenAI applications.
- Experience implementing AI governance, explainability, and responsible AI practices.
- Strong understanding of enterprise software architecture and distributed systems.
Preferred Qualifications
- Experience with agentic AI systems and orchestration frameworks.
- Experience building RAG-based AI systems.
- Familiarity with AI platform engineering and scalable AI infrastructure.
- Contributions to AI research, open-source projects, or technical publications.
- Experience working with enterprise clients in regulated industries.
Key Skills
Technical Skills
- Machine Learning & Data Science
- Large Language Models (LLMs)
- Generative AI systems
- AI agents and agentic framework
- MLOps and model lifecycle management
- AI governance and explainability
Professional Skills
- Strong analytical and problem-solving capabilities
- Excellent communication and presentation skills
- Ability to simplify complex AI concepts for diverse audiences
- Collaborative mindset and ability to work effectively within teams
- Client-facing professionalism and credibility
Work Environment
- Full-time in-office role with collaboration across engineering and client teams.
- Weekly client visits for workshops and solution design sessions.
- High collaboration with data scientists, engineers, architects, and business stakeholders.
What Success Looks Like in This Role
- Successfully designed and deliver production-grade AI systems.
- Become a trusted AI advisor to both internal teams and client stakeholders.
- Ensure responsible and governed adoption of AI technologies.
- Help organizations translate GenAI innovation into real operational value.
Orion is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, gender identity or expression, pregnancy, age, national origin, citizenship status, disability status, genetic information, protected veteran status, or any other characteristic protected by law.
Candidate Privacy Policy
Orion Systems Integrators, LLC and its subsidiaries and its affiliates (collectively, “Orion,” “we” or “us”) are committed to protecting your privacy. This Candidate Privacy Policy (orioninc.com) (“Notice”) explains:
- What information we collect during our application and recruitment process and why we collect it;
- How we handle that information; and
- How to access and update that information.
Your use of Orion services is governed by any applicable terms in this notice and our general Privacy Policy.
Ready to apply?
Apply to Orion Innovation
Overview of 66degrees
66degrees is an end-to-end AI transformation partner that guides enterprises from complex business challenges to clear, quantifiable outcomes. Our company is the culmination of several successful firms, each a leader in its own right in cloud, artificial intelligence, and data. This convergence of talent and expertise is how we help businesses reach their own "inflection point," where chaotic data becomes a strategic asset, complexity becomes clarity, and AI becomes an engine for growth. Our ultimate vision is to be the catalyst for a future where every business operates as an intelligent enterprise, with autonomous systems unlocking human potential.
At 66degrees, we believe in thriving through challenges and winning together. These values not only guide us in achieving our goals as a company but also for our people. We are dedicated to creating a significant impact for our employees by fostering a culture that sparks innovation and supports professional and personal growth along the way.
Overview of Role
66degrees is looking for creative, dedicated, and personable technology business professionals for a Principal Cloud Architect position. level. A Principal Cloud Architect is someone capable of designing complex, large-scale, and often "bleeding-edge" solutions. Our ideal candidate will display relentless curiosity and drive around how we organize ourselves and deploy/use technology to ensure our largest and most complex Enterprise clients IT environments drive business value. We are looking for the right fit with our growing team of Principal level Architects as we solve previously "unsolveable" problems with the scale of AI.
Responsibilities
- Build a trusted advisory relationship with strategic accounts and engage with CIO/CTO/VP IT and Business leaders
- Architectural Strategy & Governance
- Design Global Scale Systems: Lead the end-to-end architectural design of multi-region, highly available cloud ecosystems that support millions of concurrent users and petabyte-scale data processing.
- Standardize Infrastructure as Code (IaC): Establish and enforce enterprise-wide standards for IaC and config management to ensure consistent, repeatable, and audited deployments across all environments.
- Multi-Cloud & Hybrid Orchestration: Architect complex connectivity and workload portability strategies using Anthos, Private Service Connect, and Cloud Interconnects to bridge legacy on-premises systems with modern cloud services.
- Advanced AI & Data Innovation
- Operationalize Generative AI: Design production-grade RAG (Retrieval-Augmented Generation) architectures, ensuring LLMs are secure, reliably operate within capacity constraints and quotas, monitor and control token costs, and implement Enterprise security grade guardrails.
- End-to-End MLOps: Scale the implementation of automated machine learning pipelines—from ingestion to model serving—using Vertex AI (or self-hosted oss models) to reduce the time-to-market for predictive insights.
- Security, Risk & Compliance
- Zero-Trust Leadership: Design and lead the implementation of comprehensive security frameworks including BeyondCorp, VPC Service Controls, and advanced Identity Management (IAM) to protect sensitive workloads against sophisticated threats.
- Regulatory Engineering: Architect technical controls that automate compliance for global standards (e.g., SOC2, HIPAA, GDPR), ensuring the platform is "secure by design" and audit-ready at all times.
- Technical Leadership & Operational Excellence
- Complex Problem Resolution: Serve as the final technical escalation point for critical production issues, performing deep-root cause analysis on global-scale outages or performance bottlenecks.
- Financial Optimization (FinOps): Direct the cost-optimization strategy by designing high-efficiency architectures that balance performance requirements with long-term cloud spend sustainability.
- Cross-Functional Mentorship: Act as a force multiplier by mentoring other architects and engineering teams, fostering a culture of technical excellence and continuous learning.
- Lead Consultant
- Act as a technical subject matter expert, particularly regarding the Google Cloud ecosystem for business users, providing clear and concise explanations of complex concepts.
- Identify customer priorities, technical objections, and design strategies encompassing the Google ecosystem to deliver business growth and resolve blockers.
- Lead requirements gathering and project scoping.
- Solution design, problem-solving, and architecture diagramming.
- Provide domain expertise around public cloud and enterprise technology, and effectively promote Google Cloud with clients, at conferences, and online.
- Provide technical expertise to the team on continuous integration/continuous delivery, infrastructure, monitoring, alerting, and security.
- Provide recommendations on integration strategies, enterprise architectures, platforms, and application infrastructure needed to implement a complete solution for clients.
- Assist in delivering technical solutions to meet customer functional needs and improve service reliability, including CI/CD pipelines and infrastructure builds/migrations.
- Provide Engineer-to-Engineer and Architect-to-Engineer support, including whiteboard sessions and informal Q&A.
- Travel to customer sites, conferences, and other related events as required.
Qualifications
- 5+ years of GCP experience is a must. Experience in other clouds is beneficial.
- Proven experience in building, architecting, designing, and implementing globally distributed cloud-based systems, with a strong understanding of API-first design principles and API management platforms.
- Extensive experience with security (zero trust) and networking in cloud environments
- Capable of advising and implementing CI/CD practices to clients using tools such as GitHub, GitLab, Cloud Build, and Cloud Deploy and concepts such as GitOps and GitFlow.
- Experience in containerizing workloads using Kubernetes, Docker, Helm, and Artifact Registry.
- Knowledge of technology solutions and ability to learn emerging technologies, methodologies, and solutions in the Cloud/IT technology space.
- Ability to work cross-functionally, engage and influence audiences.
- Excellent organizational skills and customer-facing communication.
- Proficiency in documentation and knowledge transfer using remote meetings, written documents, and technical diagrams slide decks.
- Experience in implementing hybrid connectivity using VPN or Cloud Interconnect is a plus.
- GCP Credentials: Professional Cloud Architect Certification plus any other Professional Cert (Data Engineer preferred) or L400 Generative AI skill badge. Additional certifications Kubernetes (CKA, CKS), or Terraform strongly recommended
- A Bachelor's degree in Electronics Engineering, Data Science, Information Technology, Business Intelligence, Computer Science, or a related field.
66degrees is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to actual or perceived race, color, religion, sex, gender, gender identity, national origin, age, weight, height, marital status, sexual orientation, veteran status, disability status or other legally protected class.
AI Transparency & Disclosure
As an AI transformation partner, 66degrees leverages intelligent solutions to enhance our recruitment experience. We utilize AI tools—including LinkedIn Recruiter’s Hiring Assistant and interview transcription technologies—to assist with sourcing, role analysis, and capturing interview highlights.
These tools augment our process, but we "Commit to Our Craft" by ensuring all final hiring decisions are made by our human Talent Team. By applying, you acknowledge the use of these technologies to help us "Win Together" in finding the best fit for our team.
Ready to apply?
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Federal AI Solutions Engineer
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Empower, Innovate, Impact! At Team A-TEK, we EMPOWER people to drive INNOVATION that IMPACTS mission!
A-TEK operates at the intersection of mission and innovation by applying our deep domain expertise across the federal markets. Embracing our digital-first strategy, A-TEK provides enhanced capabilities in application development, digital transformation, enterprise IT, and scientific services. Our solutions are designed to modernize, automate, secure, protect, and enhance the operations of our federal clients, ensuring they stay ahead in a rapidly evolving digital landscape.
Our work is fueled by a passion to serve our clients’ needs and to protect the safety and welfare of Americans. That passion shapes how we nurture our most valuable asset – Our Employees. A-TEK actively cultivates the talent that drives our success and fosters a creative, challenging, and mission-driven work environment for current and future employees.
A-TEK is seeking a highly technical Federal AI Solutions Engineer to design, build, and operationalize mission-focused, outcome-driven solutions across AWS and Azure. This role is responsible for building both the cloud platform foundation, and the mission applications that run on it, leveraging LLMs, agentic architectures, automation frameworks, and leading-edge technologies.
In addition to engineering responsibilities, this role serves as a deep technical escalation point for A-TEK’s front-line delivery teams, helping resolve complex issues they encounter with cloud services, AI pipelines, data integration, agent frameworks, and automation.
This position sits at the center of A-TEK’s DigitalShift capability and drives rapid prototyping that can be reused, scaled, and transitioned into government missions.
This role is remote with occasional on-site presence at our federal client sites, therefore only Continental US applicants will be considered. The ability to obtain and retain a public trust clearance is required for this role.
Key Responsibilities
Mission-Focused Pilot Development
- Design, build, and deploy agentic AI pilots that demonstrate measurable mission impact using:
- Strands, LangChain, LlamaIndex, Semantic Kernel, CrewAI, or equivalent frameworks
- AWS Bedrock, Azure OpenAI, and multi-LLM orchestration
- Develop end-to-end prototypes integrating:
- Cloud-native services
- Federal or enterprise data sources
- APIs and microservices
- Enterprise authentication & security controls
- Implement prompting strategies, tool orchestration, reasoning loops, planning/execution agents, and autonomous workflows.
Internal Platform Engineering
- Build, maintain the internal AWS, and Azure environments used for A-TEK’s rapid pilot development:
- Infrastructure-as-code (Terraform/CDK/Bicep)
- Container services (ECS, EKS, AKS)
- Secure networking, identity, and data pipelines
- Develop reusable accelerators, starter kits, templates, and reference architectures.
Technical Escalation & Delivery Support
- Serve as a hands-on SME supporting client-facing teams when they encounter complex technical blockers involving:
- Cloud migrations
- AI/ML integration
- GenAI agent behavior issues
- Vector databases & RAG pipelines.
- CI/CD & automation workflows
- Provide architectural guidance and troubleshoot issues across the engineering lifecycle.
Collaboration & Knowledge Sharing
- Work closely with:
- Cloud, Cyber, Data Intelligence, and Agile Engineering Centers of Excellence
- Program managers and solution architects.
- Delivery teams and capture/proposal teams
- Produce internal documentation, patterns, and best practices to continuously expand A-TEK’s technical knowledge base.
Compliance & Governance
- Ensure all pilots and internal platforms adhere to:
- NIST AI RMF, FedRAMP, Zero Trust principles.
- Secure coding, privacy, ethical AI, and accessibility guidelines
- Implement logging/monitoring for auditability and responsible AI operations.
Qualifications:
Required
- Bachelor’s degree in Computer Science, Data Science, Engineering, or related field
- 3–5 years of hands-on software development experience (Python preferred; Node.js/Java acceptable)
- Experience building applications on AWS and/or Azure.
- Associate level or higher Solutions Architect certification in AWS or Azure
- Strong understanding of LLM APIs and ecosystems (e.g., OpenAI, Anthropic, AWS) Bedrock, Azure OpenAI
- Experience with vector databases (e.g., Pinecone, Weaviate, Milvus, FAISS)
- Ability to design and debug distributed cloud systems and AI-enabled applications.
- Strong communication skills: able to explain complex topics to A-TEK delivery teams, leadership, and partners.
Preferred
- Experience developing agentic AI systems.
- Familiarity with Containers, Serverless, Event-Driven Architecture
- Experience working in or supporting secure federal environments.
- Exposure to MLOps, DevSecOps, or continuous ATO practices
- Prior experience building reusable internal platforms or accelerators.
Compensation
Salary Range: $135,000 – $150,000 annually (commensurate with experience)
- Benefits: Health, dental, and vision insurance; 401(k) with employer match; paid time off; professional development opportunities.
Candidates may use tools (including AI) for proofreading or formatting; however, using any tool to fabricate, exaggerate, or misrepresent qualifications, experience, or work product is not permitted. We may assess application materials for job-related technical depth, internal consistency, and demonstrated hands-on experience, including through follow-up questions, skills assessments, or reference checks.
Misrepresentation or falsification may result in removal from further consideration. Candidates who need a reasonable accommodation in the application or interview process may request one.
A-TEK, Inc. is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or status as a qualified individual with a disability, or Vietnam era or other protected Veteran status. Verification of education may be requested before or during the hiring process.
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Senior Backend Software Engineer, ObservoAI
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Our Purpose
At SentinelOne, we are driven by a clear purpose: to give the advantage to those who secure our future. As AI reshapes how organizations build, operate, and innovate, the responsibility to protect them becomes more critical than ever. When you join SentinelOne, your work helps protect global enterprises, critical infrastructure, and the technologies shaping tomorrow. If you are motivated by meaningful challenges and want your impact to be real, measurable, and global, you will find purpose here.
About Us
SentinelOne is a company at the intersection of AI and security, pioneering a new operating model for cybersecurity. Our AI-native platform unifies protection across endpoint, cloud, identity, data, and AI systems to deliver autonomous detection and response with clarity and speed. By combining real-time analytics, intelligent automation, and a unified data foundation, we reduce noise, simplify complexity, and empower security teams to focus on what truly matters.
Our teams are builders, problem-solvers, and innovators committed to shaping the future of security. If you are excited to solve hard problems alongside talented, mission-driven people, we invite you to help us build a safer future for humanity.
What Are We Looking For?
We’re looking for people who are relentlessly curious and committed to continuous learning. AI is reshaping every function across our business, and we enable every team member, regardless of role or level, to build fluency in AI tools and concepts. Those who thrive here actively seek out new solutions, experiment thoughtfully, and apply what they learn to drive better, faster, smarter outcomes.
As a Senior Software Engineer, you will be tasked with leading the architectural design and technical strategy for high-performance systems that process massive volumes of telemetry data while reducing costs and improving insights for enterprise customers. You will drive technical excellence and lead complex engineering initiatives at scale for the Observo.ai team, our cutting-edge AI-driven data pipeline optimization platform.
What Will You Do?
Primary responsibilities include:
- Lead the architectural design and technical roadmap for scalable, high-performance data processing pipelines capable of handling petabyte-scale telemetry data (logs, metrics, traces).
- Drive the development and optimization of ML-driven data routing and transformation engines to reduce customer data volumes by 80%+ while architecting real-time analytics systems using advanced machine learning and LLMs.
- Design cloud-native microservices and APIs that integrate seamlessly with major observability platforms (Splunk, Elastic, Datadog) while establishing robust monitoring, alerting, and observability solutions.
- Lead cross-functional technical initiatives and decision-making forums, collaborating with Product, Data Science, and DevOps teams to translate strategic vision into technical solutions and company-wide standards.
- Provide technical leadership and mentorship to senior and junior engineers, driving system performance and reliability optimization while establishing engineering best practices and culture.
What Skills and Knowledge Will You Bring?
Ideal candidates will have:
- 5+ years of software engineering experience focused on distributed systems, data engineering, or ML infrastructure with expert-level proficiency in Go, Rust, or Java.
- Extensive experience with cloud platforms (AWS, GCP, Azure), container orchestration (Kubernetes), and a proven track record leading and scaling data pipelines using Kafka, Spark, or Flink.
- Deep expertise in database technologies (SQL and NoSQL) and advanced experience with machine learning frameworks (TensorFlow, PyTorch) and MLOps practices for production ML systems.
- Expert knowledge of observability tools and standards, including Prometheus, Grafana, ELK stack, OpenTelemetry, and Parquet, alongside extensive experience with Infrastructure as Code (Terraform).
- Strong leadership and technical communication skills, with a track record of mentoring engineers, planning technical strategy, and driving decisions across multiple teams and stakeholders.
Why SentinelOne?
AI is redefining how the world operates and rewriting the rules of security in real time, and SentinelOne was built for this moment. From day one, we architected an AI-native platform designed to operate at machine speed, not as an add-on to legacy systems but as the foundation itself. If you want to build where innovation and impact move together, this is that place.
We invest in our Sentinels with comprehensive, competitive benefits designed to support you and your family:
- Medical, Vision, Dental, 401(k), Commuter, Health and Dependent FSA
- Unlimited PTO
- Industry-leading gender-neutral parental leave
- Paid company holidays
- Paid sick time
- Employee stock purchase program
- Disability and life insurance
- Employee assistance program
- Gym membership reimbursement
- Cell phone reimbursement
- Numerous company-sponsored events, including regular happy hours and team-building events
This U.S. role has a base pay range that will vary based on the location of the candidate. For some locations, a different pay range may apply. If so, this range will be provided to you during the recruiting process. You can also reach out to the recruiter with any questions.
SentinelOne is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.
SentinelOne participates in the E-Verify Program for all U.S. based roles.
Ready to apply?
Apply to SentinelOne
About Turing
Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises looking to deploy advanced AI systems. Turing accelerates frontier research with high-quality data, specialized talent, and training pipelines that advance thinking, reasoning, coding, multimodality, and STEM. For enterprises, Turing builds proprietary intelligence systems that integrate AI into mission-critical workflows, unlock transformative outcomes, and drive lasting competitive advantage.
Recognized by Forbes, The Information, and Fast Company among the world’s top innovators, Turing’s leadership team includes AI technologists from Meta, Google, Microsoft, Apple, Amazon, McKinsey, Bain, Stanford, Caltech, and MIT. Learn more at www.turing.com
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Location |
Remote / Hybrid (HQ visits as needed) |
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Experience |
5 + years in software engineering; 2 + years in GenAI |
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Engagement |
Full-Time, Permanent |
ABOUT THE ROLE
We are looking for a talented Sr. GenAI Engineer who sits at the intersection of knowledge engineering, agentic AI, and data intelligence. In this role you will design and operate AI agents that traverse, reason over, and enrich large-scale knowledge graphs — then extend that context dynamically using live data sources such as the web, enterprise APIs, and structured databases.
The ideal candidate is deeply comfortable with graph data models, LLM orchestration frameworks, and retrieval-augmented pipelines. Bonus points if you have experience working in trade-craft or intelligence-adjacent environments where provenance, precision, and adversarial robustness are non-negotiable.
KEY RESPONSIBILITIES
Knowledge Graph Engineering
- Design, build and maintain large-scale property graphs and RDF triplestores (Neo4j, Amazon Neptune, Stardog, or equivalent).
- Develop and govern ontologies, taxonomies, and entity-relationship schemas that reflect real-world domain semantics.
- Implement graph ingestion pipelines that extract, transform, and link entities from structured, semi-structured, and unstructured data.
- Optimise graph traversal queries (Cypher, SPARQL, Gremlin) for sub-second response at production scale.
- Train and deploy graph neural networks (GNNs) for node classification, link prediction, and subgraph retrieval - Maintain model retraining workflows triggered by graph drift or coverage degradation.
Agentic AI Systems
- Architect and implement autonomous agents that plan multi-step reasoning chains over knowledge graph data using LLMs (GPT-4o, Claude, Gemini, or open-source equivalents).
- Build graph-aware Retrieval-Augmented Generation (RAG) pipelines that blend structured graph context with unstructured document retrieval.
- Design tool-use and function-calling layers so agents can query live data sources — web search, REST/GraphQL APIs, relational databases — to extend or verify graph knowledge.
- Implement agent memory, reflection, and self-correction loops to improve reliability over multi-hop tasks.
Context Enrichment & Data Fusion
- Integrate web scraping, news feeds, and open-source intelligence (OSINT) sources to keep the knowledge graph current.
- Build entity resolution and deduplication components that merge data from heterogeneous sources into a consistent graph.
- Develop confidence-scoring and provenance-tracking mechanisms so downstream consumers understand the reliability of any piece of context.
MLOps & Production Readiness
- Package agents as scalable microservices; instruments with observability tooling (tracing, latency, token cost).
- Collaborate with platform engineers to deploy workloads on cloud-native infrastructure (AWS / GCP / Azure).
- Maintain evaluation harnesses that measure agent accuracy, hallucination rate, and graph coverage over time.
REQUIRED SKILLS & EXPERIENCE
- 5 + years of professional software engineering with strong Python (or Java / Kotlin) proficiency.
- Hands-on production experience with at least one major graph database — Neo4j, Amazon Neptune, TigerGraph, or comparable.
- Demonstrated knowledge of graph query languages like Cypher, SPARQL, or Gremlin — at production query complexity.
- Direct experience building LLM-powered agents or pipelines using frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, or Semantic Kernel.
- Solid understanding of RAG architectures: chunking strategies, vector stores (Pinecone, Weaviate, pgvector), hybrid retrieval, and re-ranking.
- Familiarity with prompt engineering, few-shot learning, and LLM evaluation techniques.
- Experience integrating external data sources via APIs, web scraping (Playwright / Scrapy), or streaming pipelines (Kafka / Kinesis).
- Working knowledge of containerisation (Docker, Kubernetes) and CI/CD pipelines.
- Familiarity with graph export formats - at least one GraphML, RDF/OWL, or JSON-LDExperience integrating GNN-derived features into vector stores or RAG pipelines
PREFERRED QUALIFICATIONS
- Advanced degree (MS / PhD) in Computer Science, Information Science, Computational Linguistics, or a related field.
- Experience in intelligence, defence, or trade-craft environments — working with OSINT, link analysis, entity disambiguation, or signals intelligence data.
- Understanding of access-control models for sensitive graph data (need-to-know, compartmentalisation, provenance labelling).
- Familiarity with knowledge representation standards like OWL, SHACL, RDF-star, JSON-LD, W3C PROV.
- Experience with fine-tuning or instruction-tuning open-source LLMs (Llama, Mistral, Falcon) for domain-specific tasks.
- Background in network-analysis algorithms: centrality, community detection, path-finding, anomaly detection on graphs.
- Contributions to open-source graph or GenAI projects; published research or technical blog presence.
- Active or adjudicatable security clearance (Secret or above) — strongly preferred for trade-craft assignments.
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★ Trade-Craft Experience — A Significant Plus Candidates with backgrounds in intelligence analysis, signals intelligence, law enforcement data fusion, or related trade-craft disciplines are strongly encouraged to apply. Understanding of link analysis, entity disambiguation under adversarial conditions, handling classified or compartmentalized data, and mission-driven product constraints will set you apart. |
Values
- We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value.
- We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection
- We are Al forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity.
Advantages of joining Turing
- Amazing work culture (Super collaborative & supportive work environment; 5 days a week)
- Awesome colleagues (Surround yourself with top talent from Meta, Google, LinkedIn etc. as well as people with deep startup experience)
- Competitive compensation
- Flexible working hours
Don’t meet every single requirement? Studies have shown that women and people of color are less likely to apply to jobs unless they meet every single qualification. Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace and celebrate authenticity, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.
For applicants from the European Union, please review Turing's GDPR notice here.
Ready to apply?
Apply to TuringOctus
Octus is a leading global provider of credit intelligence, data, and analytics. Since 2013, tens of thousands of professionals across hedge fund, investment banking, management consulting, and law firm verticals have come to rely on Octus to make better, faster, and more confident decisions in pace with the fast-moving credit markets.
For more information, visit: https://octus.com/
Working at Octus
Octus hires growth-minded innovators and trailblazers across the globe to drive our business and culture. Our core values – Action Oriented, Customer First Mindset, Effective Team Players, and Driven to Excel – define an organizational ethos that’s as high-performing as it is human. Among other perks, Octus employees enjoy competitive health benefits, matched 401k and pension plans, PTO, generous parental leave, gym subsidies, educational reimbursements for career development, recognition programs, pet-friendly offices (US only), and much more.
Role
Octus is seeking a Principal Data Engineer to roll up their sleeves and build scalable, production-grade data pipelines and infrastructure. You'll be a hands-on technical leader — writing code daily, solving hard engineering problems, and helping elevate the team around you through doing. Spanning Snowflake, Databricks, and AWS, you'll be deeply involved in the day-to-day development of the data platform that powers Octus's products, data, and automation initiatives. The ideal candidate is an expert in Python and SQL who thrives in an execution-focused environment and has deep experience building modern data pipelines and lakehouse solutions.
Responsibilities
- Build and maintain end-to-end data pipelines — from raw ingestion through transformation and delivery — across diverse data sources (APIs, web data, internal feeds, etc.).
- Hands-on development of scalable, production-grade pipelines within Databricks, including Delta Lake table management, Workflows, and cluster optimization.
- Build and maintain data models, schemas, and transformation logic in Snowflake, optimizing for performance and reliability.
- Develop and manage Databricks environments including Unity Catalog, Delta Live Tables, and integration patterns that support both internal data consumers and external sharing use cases.
- Build and manage orchestration workflows using AWS services (MWAA/Airflow, Lambda, ECS, SQS, MSK) and Databricks-native orchestration where appropriate.
- Implement and maintain infrastructure as code (IaC) using Terraform, ensuring reproducibility and compliance with cloud standards.
- Establish and enforce best practices in data modeling, schema design, and ETL/ELT processes for high-volume structured and semi-structured data across Snowflake and Databricks.
- Ensure data quality, lineage, and observability through automated testing, monitoring, and alerting across all pipeline layers.
- Collaborate closely with technology leadership to align data platform development with business strategy and product goals.
- Stay at the forefront of industry trends in data engineering, lakehouse architecture, and cloud-native data platforms.
Requirements
- Strong foundation in software engineering principles, including SOLID design, modularity, and scalability.
- Expert proficiency in Databricks, including Delta Lake, Unity Catalog, Delta Live Tables, MLflow, and Databricks Workflows.
- Deep experience with Snowflake, including data modeling, performance optimization, and integration with upstream/downstream pipeline tooling.
- Expert proficiency in Python for data pipeline and automation development.
- Advanced SQL skills with experience optimizing complex queries and data models at scale.
- Proven experience designing and maintaining cloud-native data pipelines on AWS (e.g., MWAA/Airflow, Lambda, ECS, SQS, Glue, S3, Redshift, etc.).
- Experience implementing and managing Terraform or similar IaC frameworks.
- Strong understanding of lakehouse architecture patterns, data ingestion, transformation, and orchestration, including familiarity with ML/AI pipeline integration patterns.
- Familiarity with CI/CD pipelines, automated testing, and modern DevOps practices.
- 8+ years of experience in data engineering or backend development, with a focus on scalable data solutions.
- Demonstrated experience leading data infrastructure projects end-to-end and mentoring senior engineers.
- Familiarity with containerization (Docker) and workflow orchestration best practices.
- Excellent communication, collaboration, and problem-solving skills.
Nice to Have
- Experience with streaming data technologies (Kafka, Kinesis, Flink).
- Exposure to ML/AI pipeline patterns (feature stores, experiment tracking, model serving) and MLOps tooling, particularly in a cross-functional team environment.
- Experience integrating data quality and observability tools.
- Experience with Databricks as a data sharing and collaboration platform (Delta Sharing, Marketplace).
- Familiarity with Claude Code or similar AI-powered developer tools for accelerating pipeline development and code workflows.
At Octus, we consider a range of factors in connection with compensation decisions, including experience, skills, location, and our business needs and limitations. As a result, compensation may vary within and across similar roles and positions. Please note that the salary range information below is a good faith estimate for this position and actual compensation for any individual may fall outside this range if warranted by the circumstances applicable to that individual. If we identify a role that would be suitable for a broader range of skills and experience such that we would consider hiring at multiple levels then the range listed below may reflect that breadth.
The salary range estimate for this position is $175,000 - $220,000
The actual compensation will be at Octus' sole discretion and will be determined by the aforementioned and other relevant factors.
Equal Employment Opportunity
Octus is committed to providing equal employment opportunities to all employees and applicants for employment without regard to race, colour, religion, sex, sexual orientation, gender identity, national origin, age, disability, genetic information, marital status, pregnancy, veteran status, or any other legally protected status. We strive to create an inclusive and diverse work environment where all individuals are valued, respected, and treated fairly. We believe that diversity enriches our workplace and enhances our ability to innovate and succeed.
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Solutions Architect - AI
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Robots & Pencils is seeking a seasoned AWS AI Solutions Architect to lead the design and delivery of complex, enterprise-grade generative and agentic AI systems built on Amazon Web Services. You will architect scalable, secure, and production-ready AI platforms leveraging Amazon Bedrock, Amazon Bedrock AgentCore, AWS Strands Agents, AWS AgentCore Gateway, Nova Forge, Nova 2 Sonic, and related AWS AI/ML services.
As an AWS AI Solutions Architect, you will serve as a strategic technical advisor—translating ambiguity into structured AWS-native architectures, validating designs through hands-on prototyping, and ensuring every solution aligns with the AWS Well-Architected Framework (including ML Lens) while delivering measurable business value.
Key Responsibilities
Client Engagement & AWS Solutions Architecture
- Serve as the primary AWS AI architecture partner for strategic clients, driving generative and agentic AI system design from discovery through production.
- Lead architecture design using Amazon Bedrock (including foundation models and custom models), Bedrock AgentCore, AWS Strands Agents, and AWS AgentCore Gateway.
- Design advanced RAG, Agentic RAG, and multi-agent orchestration architectures leveraging AWS-native services such as Lambda, Step Functions, API Gateway, DynamoDB, Aurora (pgvector), and OpenSearch.
- Produce AWS reference architectures, architecture decision records (ADRs), and implementation roadmaps aligned to business objectives.
- Validate feasibility through hands-on prototyping in Python using Bedrock SDKs, SageMaker, and serverless services.
- Ensure architectures follow AWS security best practices (IAM, KMS, VPC, PrivateLink) and cost optimization principles.
Outcome Ownership & Business Impact
- Own architectural integrity from concept through production deployment on AWS.
- Align solutions with AWS Well-Architected Framework pillars: Operational Excellence, Security, Reliability, Performance Efficiency, Cost Optimization, and Sustainability.
- Guide clients through tradeoff decisions across model selection (Bedrock FMs vs custom SageMaker models), latency, cost, governance, and compliance.
Accelerate time-to-value through reusable AWS accelerators, Infrastructure as Code (CloudFormation/Terraform/CDK), and CI/CD automation.
- Continuously evaluate emerging AWS AI capabilities (Nova Forge, Nova 2 Sonic, Bedrock updates, and new AgentCore capabilities).
Engineering Leadership & Delivery Excellence
- • Provide architectural oversight to Forward Deployed Engineers and AWS delivery teams.
- Establish best practices for MLOps on AWS including model lifecycle management, monitoring, and observability using SageMaker, CloudWatch, CloudTrail, and AWS Config.
- Define governance, responsible AI guardrails, Bedrock Guardrails configuration, and security controls for enterprise environments.
- Mentor engineers on AWS AI service integration, distributed systems design, and secure multi-account strategies.
- Make principled tradeoffs under constraints related to privacy, compliance (SOC2, HIPAA, GDPR), cost, and operational complexity.
Cross-Functional Collaboration
- Partner with internal product, engineering, research, and customer success teams to evolve AWS-based AI offerings.
- Contribute AWS reference architectures and reusable infrastructure modules to internal accelerators.
- Support pre-sales engagements including architecture workshops, AWS migration strategy, and solution scoping.
- Collaborate across distributed teams and client stakeholders across North America.
Required Skills & Qualifications
- Bachelor’s degree in Computer Science, Engineering, or equivalent experience.
• 7–10+ years of experience in software engineering or cloud architecture with deep AWS ownership.
• Deep expertise in Amazon Bedrock, Bedrock AgentCore, AWS Strands Agents, AgentCore Gateway, and related AWS AI services.
• Strong familiarity with SageMaker (training, deployment, pipelines), deep learning fundamentals, and model fine-tuning strategies.
• Experience architecting RAG, multi-agent, and orchestration systems using AWS-native services.
• Strong knowledge of distributed systems, event-driven architectures, and serverless patterns.
• Proficiency with Infrastructure as Code (AWS CDK, CloudFormation, Terraform).
• Hands-on development capability in Python and AWS SDKs.
• Experience implementing observability and monitoring strategies in AWS environments.
• Proven success leading enterprise-scale AWS transformations.
• Exceptional communication skills for both technical and executive audiences.
• AWS Professional Certifications highly preferred (AWS Solutions Architect – Professional, AWS DevOps Engineer – Professional).
Nice to Have
- AWS Specialty certifications (Machine Learning – Specialty, Security – Specialty).
• Experience with advanced agentic reasoning patterns (ReAct,CoT, Tree-of-Thoughts) implemented on Bedrock.
• Experience building secure multi-account AWS organizations using Control Tower.
• Exposure to data engineering services such as Glue, Redshift, Lake Formation.
• Consulting or professional services background.
Personal Competencies
- Accountability – Owns AWS architectural direction and client outcomes with rigor.
• Adaptability – Rapidly adopts new AWS AI releases and evolving generative AI capabilities.
• Collaboration – Builds trust across engineering and executive stakeholders.
• Execution-Focused – Balances innovation with production-ready AWS delivery.
• Innovation-Minded – Experiments responsibly with emerging AWS AI services.
• Craftsmanship – Designs secure, scalable, and well-documented AWS systems.
• Leadership with Courage – Drives architectural alignment in complex environments.
• Comfort in Ambiguity – Translates unclear AI requirements into AWS-native solution architectures.
Why Join Robots & Pencils?
We build smart systems for a human world — blending creativity, engineering, and AWS-powered AI to help organizations reimagine how they work. As an AWS AI Solutions Architect, you will shape enterprise-scale generative and agentic AI platforms using the most advanced AWS services available. You will define architectures that deliver measurable business value, mentor teams, and directly influence the evolution of our AWS AI practice.
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[2026] Senior Machine Learning Engineer, Natural Language Processing - PhD Early Career
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Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators.
At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there.
A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone.
Natural Language Processing (NLP) is central to enabling massive-scale communication, creation, and safety across the Roblox platform. This role offers the unique opportunity to build and deploy cutting-edge NLP, speech, and generative AI models that operate at an unprecedented scale, impacting hundreds of millions of daily users.
You will solve an extremely diverse range of high-scale language-related problems—from real-time moderation of voice and text to automatically localizing experiences and empowering users through LLM-driven creation tools. We combine cutting-edge research with large-scale engineering to bridge experimentation and production, designing algorithms that shape the next generation of language services for our immersive, user-generated content platform.
Teams Hiring for This Role
- Safety AI Systems: Dedicated to building end-to-end ML systems for maintaining civility and safety across the platform, operating at massive scale. This includes:
- Real-time Moderation: Building world-class NLP and speech models for real-time moderation of voice and text (processing over 6 billion messages daily) and advanced interventions that measurably improve user civility.
- Critical Harms & Advanced Detection: Developing specialized LLM agents, behavioral analysis, and graph systems for detecting and preventing rare, high-risk scenarios (e.g., child safety, terrorism), requiring adversarial thinking and multi-step reasoning.
- Safety Data Quality: Ensuring all Safety AI systems are robust by managing the core data infrastructure, MLOps, and Active Learning initiatives for continuous model improvement.
You Will
- Design and implement deep learning-based NLP and speech solutions that address problems across Roblox, from creation to safety.
- Develop advanced models, including Large Language Models (LLMs), machine translation, and generative AI, for user interactions, content creation, and moderation.
- Have the independence and end-to-end responsibility to develop NLP/ML-based services that are scalable and resilient.
- Be a technical bar-raiser for cutting-edge ML technology, high code quality, and architectural designs.
- Work backward from user and product needs to deliver ML solutions that drive engagement, safety, and ecosystem growth.
You Have
- Possessing or pursuing a Ph.D. in Computer Science, Computer Engineering, Mathematics, Statistics, or a related technical field, with a thesis aligned to Roblox’s research areas.
- Expertise in one or more areas: NLP, Speech Models, Large Language Models, Machine Translation, or Generative AI (including diffusion models).
- Experience with transformer-based model design, training, serving, and product integration.
- A strong research track record, evidenced by multiple publications and presentations in top-tier, peer-reviewed venues (e.g., ACL, EMNLP, Interspeech, ICML, NeurIPS).
- Proficiency in one or more programming languages (e.g., Python, C++, Go, Java) and experience building and optimizing large-scale systems.
You may redact age, date of birth, and dates of attendance/graduation from your resume if you prefer.
As you apply, you can find more information about our process by signing up for Speak_. You'll gain access to our practice assessment, comprehensive guides, FAQs, and modules designed to help you ace the hiring process.
For roles that are based at our headquarters in San Mateo, CA: The starting base pay for this position is as shown below. The actual base pay is dependent upon a variety of job-related factors such as professional background, training, work experience, location, business needs and market demand. Therefore, in some circumstances, the actual salary could fall outside of this expected range. This pay range is subject to change and may be modified in the future. All full-time employees are also eligible for equity compensation and for benefits as described on this page.
Roles that are based in an office are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday (unless otherwise noted).
Roblox provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Roblox also provides reasonable accommodations to candidates with qualifying disabilities or religious beliefs during the recruiting process.
For US based roles only, please note the Company may not be able to employ candidates for this role who have United States work authorization related to certain U.S. visa categories, or support future H-1B sponsorship at this time.
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Senior Engineering Manager, AI Platform
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Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators.
At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there.
A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone.
The AI Platform team is building the unified platform that enables machine learning at a massive scale across all products and services. As a Senior Engineering Manager for the AI Platform, Data team, you will lead the development of the high-leverage data platform used by AI engineers, machine learning scientists, and product developers. You will be responsible for defining the long-term vision, strategy, and execution for the data foundation that powers the next generation of AI-driven products. This includes work on cutting-edge technologies like vector databases and knowledge graphs to enhance our data capabilities for advanced AI use cases.
You Will:
- Lead and grow a high-performing team of software engineers, fostering a culture of ownership, collaboration, and engineering excellence.
- Define the roadmap, strategy, and execution plan for the GenAI Platform which handles LLM and agent infrastructure.
- Collaborate with AI engineering, machine learning science, and product teams to understand their data needs and deliver platform capabilities that accelerate development and deployment of traditional AI and Generative models.
- Drive architectural decisions and set technical standards for reliability, scalability, and performance
- Oversee the end-to-end development life cycle, ensuring timely delivery of high-quality, robust data solutions.
- Mentor and coach team members, providing continuous feedback and career development guidance.
- Manage cross-functional projects and communicate progress, risks, and challenges to leadership and stakeholders.
You Are:
- A seasoned engineering leader with 5+ years of management experience and 8+ years of experience building large-scale, high-performance data platforms, machine learning infrastructure, or distributed systems.
- Experienced in hiring, managing, and mentoring senior software engineers and technical leaders.
- Deeply knowledgeable about data technologies (e.g., Spark, Hadoop, Flink, Kafka, distributed databases, data warehousing) and best practices for large-scale data processing and storage.
- Skilled at driving technical strategy and roadmap planning in ambiguous and fast-paced environments.
- Able to establish strong, collaborative relationships with cross-functional partners and senior leadership.
- Passionate about fostering a positive, inclusive, and high-energy engineering culture.
- Knowledgeable in the machine learning life cycle (MLOps) and the data requirements for training, serving, and monitoring models.
- A strong communicator, both written and verbal, capable of articulating complex technical concepts to a diverse audience.
Preferred Qualifications
- A BS, MS, or PhD in Computer Science, or a related technical field.
- Experience with cloud-based data solutions (e.g., AWS, GCP, Azure).
- Experience with real-time data processing and stream computing technologies.
For roles that are based at our headquarters in San Mateo, CA: The starting base pay for this position is as shown below. The actual base pay is dependent upon a variety of job-related factors such as professional background, training, work experience, location, business needs and market demand. Therefore, in some circumstances, the actual salary could fall outside of this expected range. This pay range is subject to change and may be modified in the future. All full-time employees are also eligible for equity compensation and for benefits as described on this page.
Roles that are based in an office are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday (unless otherwise noted).
Roblox provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Roblox also provides reasonable accommodations to candidates with qualifying disabilities or religious beliefs during the recruiting process.
For US based roles only, please note the Company may not be able to employ candidates for this role who have United States work authorization related to certain U.S. visa categories, or support future H-1B sponsorship at this time.
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Senior Staff Machine Learning Engineer, ML Understanding
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We’re looking for a Senior Staff Machine Learning Engineer to lead Reddit’s next-generation user understanding initiative: building a unified, high-fidelity representation of each user that powers personalization across the platform.
This role requires deep expertise in mainstream ML user modeling approaches (e.g., large-scale embeddings, user interest modeling, affinities, behavioral signals) and the ability to reimagine these systems in the GenAI era—leveraging LLMs and foundation models to unlock step-change improvements in fidelity, adaptability, and expressiveness.
You will set the technical direction for this space, leading the design and implementation of Reddit’s core user representation layer—spanning embeddings, interest modeling, and key user attributes. You’ll ensure this foundation is scalable, reliable, and widely adopted across Feeds, Search, Notifications, and Ads, partnering closely with product, infrastructure, and downstream ML teams to drive measurable impact.
This is a high-impact role. The systems you build will shape how hundreds of millions of people experience Reddit every day—what they see, what they discover, and the communities they connect with. Your work will directly advance personalization and relevance at global scale, strengthening Reddit as a platform for meaningful connection and belonging.
What you'll do:
- Design User Understanding Strategy: Define a unified user understanding framework and strategy: how users are represented (embeddings, tags, attributes, LLM-based user profile), how they are computed, stored, and exposed. Provide thought leadership in user understanding and user modeling by setting a long-term technical vision and advancing the state-of-the-art in the field.
- Build Foundational User Models: Lead design and implementation of advanced user models, e.g. large-scale user representation learning (sequence-based, multi-interest, multi-task) that share representations across surfaces to improve personalization experience across key Reddit products e.g. Feeds, Notification, Search and Ads, balancing latency, cost, and performance.
- Reimagine user understanding with LLM/Gen-AI: Evolve user modeling beyond traditional representations by leveraging LLMs to build richer user understanding (e.g., dynamic user profiles, intent inference, semantic reasoning over user behavior). Explore how LLMs can augment or unify embeddings, attributes, and taxonomies to enable more adaptive, interpretable, and context-aware personalization.
- Ship Large Scale User Understanding as a System: Partner with platform teams to design and build core components for large-scale learning and serving: storage/retrieval for embeddings, feature pipelines, and APIs. Collaborate with ML/Ranking infra to ensure low-latency serving, high availability, and integration with MLOps systems.
- Drive Cross-Team Integration & Impact: Partner with Feeds, Notification, Search and Ads teams to drive experimentation and adoption of new user understanding models with product teams across Reddit, ensuring measurable end-to-end impact on key metrics.
- Set Technical Bar & Mentor: Mentor senior to staff engineers, lead design reviews, steward technical decisions across the user understanding domain, and champion and drive engineering processes and best practices
Who you might be:
- You have at least 10 years experience building and scaling production-grade ML systems, particularly in user modeling, large-scale representation learning, or recommender systems.
- You have a track record of driving ambiguous, high-impact initiatives from concept to production, shaping both technical direction and execution.
- You are product- and impact-oriented: you care deeply about how your work moves real metrics (e.g., engagement, retention, revenue), not just model quality.
- You bring strong fundamentals in mainstream user understanding ML approaches (e.g., representation learning, behavioral modeling, user clustering), and understand their trade-offs in real-world systems.
- You are excited about the GenAI shift and have experience (or strong intuition) applying LLMs or foundation models to evolve existing systems, going beyond incremental improvements.
- You think in systems, not just models: you consider data, training, evaluation, serving, and adoption as a cohesive whole, and design with end-to-end impact in mind.
- You influence beyond your immediate team: partnering effectively with product, infra, and other ML teams, and driving alignment across multiple stakeholders.
- You raise the technical bar: mentoring senior engineers, leading design reviews, and establishing best practices for building reliable, scalable ML systems.
- You are comfortable navigating trade-offs across quality, latency, cost, and safety, especially in large-scale, user-facing systems.
Benefits:
- Comprehensive Healthcare Benefits and Income Replacement Programs
- 401k with Employer Match
- Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
- Family Planning Support
- Gender-Affirming Care
- Mental Health & Coaching Benefits
- Flexible Vacation & Paid Volunteer Time Off
- Generous Paid Parental Leave
#LI-remote, #LI-JS5
Pay Transparency:
This job posting may span more than one career level.
In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/.
To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.
In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.
During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors.
Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.
Ready to apply?
Apply to Reddit
Senior Machine Learning Engineer, GenAI Security
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The GenAI Security team within Reddit’s Security, Privacy, Assurance, and Corporate Engineering organization protects Reddit’s GenAI usage across employee tools, internal agents, and production user-facing systems. Our mission is to secure and protect Reddit’s AI traffic and GenAI adoption by default.
We are building zero-trust, defense-in-depth systems that verify identity, permissions, data access, and semantic intent across AI workflows. A core part of this work is developing practical, high-quality ML models that detect and prevent security risks such as prompt injection, jailbreak attempts, sensitive data exfiltration, unsafe model behavior, anomalous usage, and unauthorized agent actions.
We are looking for a Senior Machine Learning Engineer to lead model development for GenAI Security and help establish strong ML practices across SPACE. This role owns the full machine learning lifecycle: problem definition, data ETL, feature engineering, model training, model evaluation, deployment, experimentation, prediction, monitoring, debugging, and retraining.
What You’ll Do
- Build and improve security-focused ML models for Reddit’s GenAI traffic, including guardrail models, semantic classifiers, anomaly detection models, and other neural network based security signals.
- Own model development end to end: define the security problem, assemble and label datasets, build ETL pipelines, engineer features, train models, evaluate quality, deploy to production, monitor performance, and retrain from production feedback.
- Use modern deep learning architectures, including neural networks, transformers, sequence models, embeddings, and model distillation where they are the right practical fit.
- Design rigorous evaluation suites for adversarial examples, hard negatives, long-context inputs, structured payloads, tool calls, multi-turn workflows, and real production traffic.
- Improve model precision, recall, latency, cost, calibration, and operational reliability for high-impact production surfaces.
- Build repeatable MLOps workflows for SPACE, including training pipelines, model lineage, artifact management, holdout evaluation, dashboards, rollback paths, and retraining loops.
- Partner closely with ML Infrastructure, LLM Gateway, DevX, Ads, Answers, Safety, Privacy, Compliance, and other Security teams to bring security models into real production workflows.
- Work pragmatically with Reddit’s evolving ML platform, using existing infrastructure where possible and building focused tooling when needed to keep model iteration moving.
- Translate security goals into measurable model outcomes and help partners understand tradeoffs between risk reduction, latency, false positives, and product impact.
- Provide technical direction to other engineers and serve as a go-to ML expert for GenAI Security and broader SPACE model needs.
Who You Might Be
- 5+ years of experience building, training, evaluating, and deploying production ML or deep learning models.
- Hands-on experience with modern ML frameworks such as PyTorch, TensorFlow, or similar.
- Strong practical understanding of the full ML lifecycle: problem definition, data ETL, feature engineering, training, evaluation, deployment, monitoring, debugging, and retraining.
- Experience building data pipelines and working with large-scale datasets.
- Experience designing rigorous model evaluations, including precision/recall/F1, false positive analysis, threshold tuning, calibration, holdout sets, regression tests, and production-quality validation.
- Experience shipping production-quality software, preferably in Python and/or Go.
- Strong communication skills and ability to explain model behavior, risk tradeoffs, and technical decisions to cross-functional partners.
- BS degree in Computer Science, Machine Learning, a related technical field, or equivalent practical experience.
- Experience in the following areas is a plus:
- Applying ML to security, privacy, trust and safety, abuse prevention, adversarial ML, or GenAI security problems.
- Training or fine-tuning neural text models for complex inputs such as long-context prompts, structured payloads, code-like content, multi-turn interactions, or tool calls.
- Production MLOps or model serving systems such as Airflow, Ray, MLflow, Triton, ONNX, Kubernetes, or similar.
- Improving model quality through labeling strategy, hard-negative mining, synthetic data generation, distillation, or active learning.
Benefits:
- Comprehensive Healthcare Benefits and Income Replacement Programs
- 401k with Employer Match
- Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
- Family Planning Support
- Gender-Affirming Care
- Mental Health & Coaching Benefits
- Flexible Vacation & Paid Volunteer Time Off
- Generous Paid Parental Leave
#LI-remote
Pay Transparency:
This job posting may span more than one career level.
In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/.
To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.
In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.
During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors.
Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.
Ready to apply?
Apply to Reddit
Who We Are:
The Machine Learning Platform team at Reddit is a high-impact team that owns the infrastructure that powers recommendations, content discovery, user and content quantification, while directly impacting other teams such as Growth, Ads, Feeds, and Core Machine Learning teams.
What You’ll Do:
As a Senior Software Engineer, you will lead the development of a large-scale GenAI Platform at Reddit.
- Contribute to the design, implementation, and maintenance of the LLM Gateway, focusing on features like unified API endpoints for internal/externally hosted LLM, rate/token limit management, and intelligent failover mechanisms to boost uptime and reliability.
- Designed and developed ML and Generative AI systems in cloud-based production environments at scale.
- Build and manage enterprise-grade RAG applications using embeddings, vector search, and retrieval pipelines.
- Implement and operationalize agentic AI workflows with tool use using frameworks such as LangChain and LangGraph.
- Drive adoption of MLOps / LLMOps practices, including CI/CD automation, versioning, testing, and lifecycle management.
- Establish best practices for observability, monitoring, evaluation, and governance of GenAI pipelines in production.
- Strong ownership mindset and platform thinking.
- Ability to lead AI platform delivery from concept to production.
Who You Might Be:
- 5+ years of experience in ML Engineering, AI Platform Engineering, or Cloud AI Deployment roles.
- Have experience operating orchestration systems such as Kubernetes at scale
- Deep experience with cloud-based technologies for supporting an ML platform, including tools like AWS, Google Cloud Storage, infrastructure-as-code (Terraform), and more
- Proficiency with the common programming languages and frameworks of ML, such as Go, Python, etc.
- Excellent communication skills with the ability to articulate technical AI concepts to non-technical stakeholders
- Strong focus on scalability, reliability, performance, and ease of use. You are an undying advocate for platform users and have a deep intuition for the genAI product development lifecycle.
- Strong knowledge of model serving, inference pipelines, monitoring, and observability for AI systems is a plus
- Strong proficiency in Python and experience with modern AI/ML frameworks (e.g. LangChain, Vertex AI Agent Builder, TensorFlow, PyTorch is a plus
Benefits:
- Comprehensive Healthcare Benefits and Income Replacement Programs
- 401k with Employer Match
- Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
- Family Planning Support
- Gender-Affirming Care
- Mental Health & Coaching Benefits
- Flexible Vacation & Paid Volunteer Time Off
- Generous Paid Parental Leave
Pay Transparency:
This job posting may span more than one career level.
In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/.
To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.
In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.
During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors.
Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.
Ready to apply?
Apply to Reddit
Staff Machine Learning Engineer, Ads Content Understanding
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Ads Content Understanding (ACU) is Reddit’s core commercial content understanding team for Ads. The team owns and produces signals that describe what Reddit content is about, how brand safe and suitable it is, and what users are trying to accomplish in commercial conversations. ACU is responsible for:
- The Knowledge Graph (entities, brands, products, and relationships across Reddit and external sources).
- Content taxonomies such as IAB, Shopify Standard Product Taxonomy, IAS, and other commercial taxonomies used for targeting, safety, and marketplace dynamics.
- Opinion mining for ads use cases: sentiment, stance, commercial intent, and other qualitative attributes of conversations.
- Shopping / product understanding: detecting product entities, product categories, and product attributes in organic conversations and aligning them with shopping catalogs.
- Signals and tags registry: a unified, governed catalog of ACU signals that powers retrieval, ranking, safety, and insights across Ads Foundations and partner teams.
We are looking for a Staff Machine Learning Engineer who will lead the Commercial Content Understanding roadmap for the Monetization org and act as the technical owner for ACU’s signals and ML systems. Roughly 50% of their time should be spent in technical leadership and mentorship (driving designs, standards, cross-team alignment), and 50% in direct hands-on work (modeling, pipelines, and debugging complex production systems).
Responsibilities:
- Provide technical leadership and mentorship to MLEs and SWEs doing ML work in ACU, acting as de facto tech lead for content understanding and signals: driving design reviews, setting technical standards, and uplifting the team’s modeling and systems craft.
- Develop evaluation systems and quality monitoring systems for content understanding signals, using SOTA LM-judge practices.
- Drive operational excellence for ACU’s ML systems by defining SLOs, alerting, and dashboards for key signals (coverage, latency, precision/recall, cost)
- Build and evolve content understanding capabilities for commercial conversations (e.g., reviews vs. recommendations vs. comparisons vs. Q&A; sentiment and stance; product entities and categories) and operationalize them as robust signals that power contextual and shopping ads, auto-targeting, new formats, and insights products.
- Lead design and implementation of signals pipelines and produce an ACU signals registry. Partner with platform teams and other content understanding teams to ensure efficient, reliable serving at Reddit scale.
- Drive LLM and modern ML best practices within ACU: define when to prompt, finetune, or distill; design evaluation and safety harnesses; and lead at least one major distillation effort to replace external APIs with in-house models.
- Operate across the full ML lifecycle (problem framing, data, modeling, evaluation, deployment, monitoring, and oncall), designing scalable, resilient MLOps pipelines and championing responsible AI (bias, safety, explainability) for ACU’s models and signals in production.
Required Qualifications:
- 7+ years of relevant MLE experience delivering production ML systems (models + pipelines + serving) at scale, ideally in large-scale content understanding domains, or Ads.
- Demonstrated Staff-level technical leadership: has driven architecture decisions, standards, and design reviews across multiple teams, and has aligned PMs, DSs, and engineers on shared ML systems or platforms without direct people-management authority.
- Excellent communication skills, with the ability to explain complex technical trade-offs to PMs, DSs, and other engineering teams, especially in ambiguous, cross-team problem spaces like Seekers/Searchers monetization.
- Strong track record building and shipping NLP / Language models / content understanding models to production (e.g., classifiers, encoders, sequence or session models), with clear business outcomes (e.g., CTR/ROAS uplift, safety improvements). Experience with commercial or intent modeling is a strong plus.
- Practical experience using LLMs in production for labeling, evaluation, or distillation (e.g., LM-as-judge, prompt-based classifiers, LLM-generated labels distilled into smaller models), including managing quality, cost, and latency trade-offs.
- Deep experience with PyTorch, TensorFlow, or similar, and production-quality code in Python (and ideally one statically typed language like Go/Java/C++). Comfortable owning training, evaluation, and deployment code end-to-end.
- Experience designing ML systems and pipelines: offline training, feature pipelines (batch/streaming), online serving, monitoring, and experimentation for high-traffic surfaces.
Benefits:
- Comprehensive Healthcare Benefits and Income Replacement Programs
- 401k with Employer Match
- Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
- Family Planning Support
- Gender-Affirming Care
- Mental Health & Coaching Benefits
- Flexible Vacation & Paid Volunteer Time Off
- Generous Paid Parental Leave
#LI-Remote
Pay Transparency:
This job posting may span more than one career level.
In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/.
To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.
In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.
During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors.
Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.
Ready to apply?
Apply to Reddit
Senior Staff Machine Learning Engineer, GenAI Platform
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Who We Are:
The Machine Learning Platform team at Reddit is a high-impact team that owns the infrastructure that powers recommendations, content discovery, user and content quantification, while directly impacting other teams such as Growth, Ads, Feeds, and Core Machine Learning teams.
What You’ll Do:
As a Senior Staff Software Engineer, you will help define and lead the vision for Reddit’s large-scale GenAI Platform, shaping the strategy, architecture, and operating model that enable teams across the company to build, deploy, and scale generative AI products with confidence.
Contribute to the design, implementation, and maintenance of the LLM Gateway, focusing on features like unified API endpoints for internal/externally hosted LLM, rate/token limit management, and intelligent failover mechanisms to boost uptime and reliability.
- Lead and execute the vision, strategy, and roadmap for Reddit’s large-scale GenAI Platform.
- Define the platform architecture and operating model that enable teams to build, deploy, and scale GenAI products reliably.
- Drive the strategy for a unified LAG Gateway supporting internally and externally hosted LLMs through consistent APIs and abstractions.
- Set the direction for core platform capabilities such as rate and token limit management, intelligent failover, and production resilience.
- Shape Reddit’s approach to an enterprise-grade RAG system
- Establish the strategic direction for agentic AI workflows and tool-use patterns across the platform.
- Own the end-to-end platform strategy from concept through production adoption and long-term evolution.
- Drive MLOps and LLMOps standards across CI/CD, testing, versioning, evaluation, and lifecycle management.
- Define best practices for observability, monitoring, governance, and operational excellence across GenAI systems.
- Partner across engineering, product, and leadership to align platform investments with company priorities and user needs.
- Champion platform thinking with a strong focus on scalability, reliability, performance, and developer experience.
- Influence technical direction across teams by turning emerging AI capabilities into a scalable platform strategy.
Who You Might Be:
- 10+ years of experience in ML Engineering, AI Platform Engineering, or Cloud AI Deployment roles.
- Have a track record of leading technical strategy and delivering AI platforms in cloud-based production environments at scale.
- Demonstrate strong execution by turning strategy into action, driving complex initiatives end to end, and consistently delivering high-quality platform outcomes.
- Bring deep experience operating Kubernetes and other orchestration systems in large-scale production environments.
- Deep experience with cloud-based technologies for supporting an ML platform, including tools like AWS, Google Cloud Storage, infrastructure-as-code (Terraform), and more
- Proficiency with the common programming languages and frameworks of ML, such as Go, Python, etc.
- Excellent communication skills with the ability to articulate technical AI concepts to non-technical stakeholders
- Strong focus on scalability, reliability, performance, and developer experience. You are an undying advocate for platform users and have a deep intuition for the genAI product development lifecycle.
- Strong knowledge of model serving, inference pipelines, monitoring, and observability for AI systems is a plus
Benefits:
- Comprehensive Healthcare Benefits and Income Replacement Programs
- 401k with Employer Match
- Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
- Family Planning Support
- Gender-Affirming Care
- Mental Health & Coaching Benefits
- Flexible Vacation & Paid Volunteer Time Off
- Generous Paid Parental Leave
Pay Transparency:
This job posting may span more than one career level.
In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/.
To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.
In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.
During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors.
Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.
Ready to apply?
Apply to Reddit
Machine Learning Engineer
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About Checkr
Checkr is building the data platform to power safe and fair decisions. Checkr’s innovative technology and robust data platform help customers assess risk and ensure safety and compliance to build trusted workplaces and communities. Checkr has over 100,000 customers including Amazon, DoorDash, Netflix, Kimpton, and Anthropic.
We’re a team that thrives on solving complex problems with innovative solutions that advance our mission. Checkr is recognized on Forbes Cloud 100 2025 List and is a Y Combinator 2024 Breakthrough Company.
About the team/role
We’re hiring an ML Engineer (P2) to build and ship the AI systems that power Checkr’s core products. This role sits on the ML team inside Checkr’s Data & ML organization within Engineering.
Checkr runs millions of background checks a year. The ML team builds the systems that make those checks faster, more accurate, and cheaper to operate: document processing, charge classification, entity resolution, and in-product intelligence. These are production services that Product Engineering depends on daily.
This is not a research role or a notebook role. You’ll own ML services end-to-end: design them, code them, deploy them, monitor them. We need someone who writes production software, builds with LLMs and APIs as first-class tools, and can tell the difference between working code and AI slop. If you’ve spent the last few years building AI-native software and you care deeply about engineering craft, we want to talk.
This role sits in the central Data & ML team within the Engineering organization. You will partner daily with Product Engineering, Product, and cross-functional teams. You’ll also contribute to Checkr’s broader AI strategy, including our initiative to deploy our agentic fleet and build scalable context with our semantic layer.
We are looking for someone based in San Francisco who has built ML systems in fast-moving, impact-first environments. Less process, more shipping. Less paperwork, more results.
What you’ll do
- Build and deploy ML/AI services. Design, develop, and ship ML models and AI systems that Product Engineering teams rely on. You write the model code, the API layer, the monitoring, and the tests. Not notebooks; production services.
- Design with LLMs and APIs. Use LLM APIs (OpenAI, Anthropic, etc.) as building blocks in production systems. You know when to call an LLM, when to fine-tune, when to use a classical model, and when to write a rule. You think about cost, latency, and quality together.
- Ship production software. Write clean, well-structured code with solid OOP, proper abstractions, error handling, and tests. Your code gets reviewed by SWEs and passes. CI/CD is how you work, not something you bolt on at the end.
- Partner with product and engineering. Translate business problems into ML solutions. Define API contracts with product engineers. Explain your approach clearly to non-ML partners and leave the room with alignment, not confusion.
- Evaluate and iterate fast. Build evaluation frameworks, run experiments, and make data-driven decisions about model and system performance. Ship and iterate; don’t wait for perfect.
- Ship AI-powered workflows. Put AI to work on your own processes: automate pipelines, build agentic workflows, and contribute reusable skills and context to Checkr’s agentic platform. The expectation is that our teams operate AI-first.
What you bring
- A Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field, or equivalent depth from experience
- 4+ years building software professionally, with at least 2 of those building ML systems that run in production
- Strong Python fluency; you write clean, testable, well-structured code with solid OOP instincts. Not scripts; software
- Hands-on experience using LLM APIs in production systems: prompt engineering, structured outputs, function calling, cost management, and evaluation
- You’ve built and maintained APIs, worked with CI/CD pipelines, and shipped code that other engineers depend on
- Comfortable with distributed systems concepts: queues, async processing, caching, horizontal scaling
- Experience with NLP tasks in production: classification, extraction, entity resolution, summarization
- Comfort with and enthusiasm for AI-assisted workflows; experience using LLMs, code-generation tools, or agentic systems in production or operational contexts is a strong signal
- You can evaluate tradeoffs: fine-tune vs. prompt, hosted vs. self-deployed, classical ML vs. LLM, rule vs. model
- Strong communication skills; you explain technical decisions clearly to engineers and non-engineers alike, without hiding behind jargon
- You use AI tools (Copilot, Claude, etc.) to move faster, but you understand every line they produce. You can spot AI slop and you don’t ship it
- An A-player mindset with a strong bias for action: you raise the bar, move with urgency, stay resilient through ambiguity, and take ownership to deliver meaningful outcomes.
Nice to have
- Experience with MLOps platforms (MLflow, SageMaker, Vertex, or similar)
- Background in document processing, OCR, or information extraction
- Experience with PySpark or large-scale data processing
- Ruby experience (Checkr’s platform runs on Rails)
- Familiarity with compliance-sensitive domains (fintech, legal tech, HR tech)
- Working knowledge of dbt, Snowflake, or modern ELT/data transformation tools
What you’ll get
- A fast-paced, low-bureaucracy environment where shipping matters more than process
- Direct exposure to executive and C-level decision-making
- A seat on the Data & ML team shaping Checkr’s AI strategy
- Learning and development allowance
- Competitive cash and equity compensation and opportunity for advancement
- 100% medical, dental, and vision coverage
- Up to $25K reimbursement for fertility, adoption, and parental planning services
- Flexible PTO policy
- Monthly wellness stipend
Pay Transparency Disclosure
One of Checkr’s core values is Transparency. To live by that value, we’ve made the decision to disclose salary ranges in all of our job postings. We use geographic cost of labor as an input to develop ranges for our roles and as such, each location where we hire may have a different range. If this role is remote, we have listed the top to the bottom of the possible range, but we will specify the target range for an exact location when you are selected for a recruiting discussion. For more information on our compensation philosophy, see our website.
At Checkr, we believe an in office work environment strengthens collaboration, drives innovation, and encourages connection. Our hub locations are Denver, CO; San Francisco, CA; Nashville, TN; and Santiago, Chile. Individuals are expected to work from the office 3+ days a week. In-office perks are provided, such as lunch five times a week, a commuter stipend, and an abundance of snacks and beverages. A relocation stipend may be available for those willing to relocate to a Checkr hub location.
Equal Employment Opportunities at Checkr
Checkr is committed to building the best product and company, which requires hiring talented and qualified individuals with a diverse set of perspectives and lived experiences. Checkr believes in hiring people of all backgrounds, including those whose histories are impacted by the justice system in accordance with local, state, and/or federal laws, including the San Francisco’s Fair Chance Ordinance.
Applicant Privacy Policy
If you are a California resident or are located in Alberta or British Columbia, our Applicant Privacy Policy applies to our collection and processing of your personal information when you apply for a role with us or otherwise participate in our recruitment process.
*Legitimate Checkr emails will always include our official domain name after the @ symbol (e.g., name@checkr.com or name@ext.checkr.com).
Ready to apply?
Apply to Checkr
Senior Software Engineer, DevOps
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Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.
ABOUT THE TEAM
Anduril Maritime delivers platforms, systems, and integrated effects in the maritime domain. Our autonomous vehicles (sub-surface and surface) are the cornerstone of these capabilities, and we continually strive to push the boundaries of the possible in terms of endurance, autonomy and mission capability. The Maritime team develops and maintains core products and payloads, and adapts and applies those products to serve a wide variety of defense, IC and commercial customers in US and international markets.
ABOUT THE JOB
As a Senior Software Engineer, DevOps on the Maritime Digital Shipbuilding team, you will build and operate the infrastructure that keeps our digital production systems running at full speed. You’ll develop and manage CI/CD pipelines, automate infrastructure with code, and deploy applications and machine learning models across cloud and edge environments with security, traceability, and reliability in mind.
You’ll work closely with software, data, and operations engineers to turn designs into working systems—streamlining development, improving performance, and keeping production stable as we scale. You’ll also collaborate with digital, manufacturing, and corporate technology teams across Anduril in a high-tech, fast-paced culture of innovation focused on solving real problems and delivering results.
If you’re driven to build systems that last, thrive on deep technical challenges, and want to see your work directly shape how we design, build, and sustain complex platforms, you’ll be helping build the future of digital shipbuilding and the next generation of maritime vehicles.
WHAT YOU'LL DO
- Build and Manage CI/CD Pipelines: Develop and maintain CI/CD pipelines using tools like GitHub Actions and Jfrog Artifactory to ensure seamless integration and deployment of machine learning models and applications.
- Infrastructure as Code (IaC): Utilize Terraform and Ansible to automate infrastructure provisioning and management on cloud platforms such as Azure, AWS, or Google Cloud Platform (GCP).
- Containerization and Orchestration: Implement containerization solutions with Docker and manage container orchestration using Kubernetes to ensure reliable deployment and scaling of applications.
- Model Management and Deployment: Set up and maintain model registries and feature stores (e.g., MLflow, Kubeflow), and manage deployment pipelines for both batch and real-time inference.
- Monitoring and Logging: Establish comprehensive monitoring and logging solutions using tools like ELK Stack (Elasticsearch, Logstash, Kibana), Prometheus, and Grafana to ensure the smooth operation of deployment environments.
- Collaborate with Cross-Functional Teams: Work closely with development, data science, and operations teams to foster collaboration and ensure the efficient and effective deployment of machine learning models.
- Optimize Performance: Utilize parallel computing frameworks such as CUDA and OpenCL to accelerate high-performance computing tasks, ensuring timely processing of large datasets and complex simulations.
REQUIRED QUALIFICATIONS
- Advanced proficiency in programming languages (Python for scripting and integration).
- Experience with CI/CD tools like GitHub Actions, Jfrog Artifactory, and Git.
- Proficiency with IaC tools (Terraform, Ansible).
- Experience with cloud platforms (Azure, AWS, GCP).
- Proficiency in containerization (Docker) and container orchestration (Kubernetes).
- Knowledge of model registries and feature stores (e.g., MLflow, Kubeflow).
- Experience with logging and monitoring tools (ELK Stack, Prometheus, Grafana).
- Understanding of parallel computing frameworks (CUDA, OpenCL).
- Strong collaboration skills and proficiency with collaborative tools (JIRA, Confluence).
- Eligible to obtain and maintain an active U.S. Secret security clearance.
PREFERRED QUALIFICATIONS
- Previous experience in a manufacturing or industrial setting.
- Familiarity with observability concepts and tools.
- Knowledge of security best practices for DevOps and MLOps.
The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. Highly competitive equity grants are included in the majority of full time offers; and are considered part of Anduril's total compensation package. Additionally, Anduril offers top-tier benefits for full-time employees, including:
Benefits
At Anduril, we invest in our people. Our comprehensive, competitive benefits package (available at little to no cost to employees) ensures you’re supported in health, recovery, and whatever comes next. For more information, Explore Our Benefits.
Protecting Yourself from Recruitment Scams
Anduril is committed to maintaining the integrity of our Talent acquisition process and the security of our candidates. We've observed a rise in sophisticated phishing and fraudulent schemes where individuals impersonate Anduril representatives, luring job seekers with false interviews or job offers. These scammers often attempt to extract payment or sensitive personal information.
To ensure your safety and help you navigate your job search with confidence, please keep the following critical points in mind:
-
No Financial Requests: Anduril will never solicit payment or demand personal financial details (such as banking information, credit card numbers, or social security numbers) at any stage of our hiring process. Our legitimate recruitment is entirely free for candidates.
- Please always verify communications:
- Direct from Anduril: If you receive an email from one of our recruiters, it will only come from an
@anduril.comaddress. - Via Agency Partner: If contacted by a recruiting agency for an Anduril role, their email will clearly identify their agency. If you suspect any suspicious activity, please verify the agency's authenticity by reaching out to contact@anduril.com.
- Direct from Anduril: If you receive an email from one of our recruiters, it will only come from an
-
Exercise Caution with Unsolicited Outreach: If you receive any communication that appears suspicious, contains grammatical errors, or makes unusual requests, do not engage. Always confirm the sender's email domain is @anduril.com before providing any personal information or clicking on links.
-
What to Do If You Suspect Fraud: Should you encounter any questionable or fraudulent outreach claiming to be from Anduril, please report it immediately to contact@anduril.com. Your proactive caution is invaluable in protecting your personal information and upholding the security and trustworthiness of our recruitment efforts.
Data Privacy
To view Anduril's candidate data privacy policy, please visit https://anduril.com/applicant-privacy-notice/.
By submitting your application, you consent to Anduril Industries using a third-party service provider to conduct pre-employment risk, integrity, and due diligence screening and assessing potential risks as part of your application process. This third-party service provider provides risk-intelligence services that may include analysis of sanctions and watchlists, adverse media, public-record information, and other lawful open-source or commercial data sources. This third-party service provider does not act as a consumer reporting agency. Use of this provider helps to ensure compliance with applicable laws and protect technology, intellectual property, and organizational security.
Ready to apply?
Apply to Anduril Industries
Senior Site Reliability Engineer
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Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.
ABOUT THE TEAM
Anduril Maritime delivers platforms, systems, and integrated effects in the maritime domain. Our autonomous vehicles (sub-surface and surface) are the cornerstone of these capabilities, and we continually strive to push the boundaries of the possible in terms of endurance, autonomy and mission capability. The Maritime team develops and maintains core products and payloads, and adapts and applies those products to serve a wide variety of defense, IC and commercial customers in US and international markets.
ABOUT THE JOB
As a Senior Site Reliability Engineer on the Maritime Digital Shipbuilding team, you will build and operate the infrastructure that keeps our digital production systems running at full speed. You’ll develop and manage CI/CD pipelines, automate infrastructure with code, and deploy applications and machine learning models across cloud and edge environments with security, traceability, and reliability in mind.
You’ll work closely with software, data, and operations engineers to turn designs into working systems—streamlining development, improving performance, and keeping production stable as we scale. You’ll also collaborate with digital, manufacturing, and corporate technology teams across Anduril in a high-tech, fast-paced culture of innovation focused on solving real problems and delivering results.
If you’re driven to build systems that last, thrive on deep technical challenges, and want to see your work directly shape how we design, build, and sustain complex platforms, you’ll be helping build the future of digital shipbuilding and the next generation of maritime vehicles.
WHAT YOU'LL DO
- Build and Manage CI/CD Pipelines: Develop and maintain CI/CD pipelines using tools like GitHub Actions and Jfrog Artifactory to ensure seamless integration and deployment of machine learning models and applications.
- Infrastructure as Code (IaC): Utilize Terraform and Ansible to automate infrastructure provisioning and management on cloud platforms such as Azure, AWS, or Google Cloud Platform (GCP).
- Containerization and Orchestration: Implement containerization solutions with Docker and manage container orchestration using Kubernetes to ensure reliable deployment and scaling of applications.
- Model Management and Deployment: Set up and maintain model registries and feature stores (e.g., MLflow, Kubeflow), and manage deployment pipelines for both batch and real-time inference.
- Monitoring and Logging: Establish comprehensive monitoring and logging solutions using tools like ELK Stack (Elasticsearch, Logstash, Kibana), Prometheus, and Grafana to ensure the smooth operation of deployment environments.
- Collaborate with Cross-Functional Teams: Work closely with development, data science, and operations teams to foster collaboration and ensure the efficient and effective deployment of machine learning models.
- Optimize Performance: Utilize parallel computing frameworks such as CUDA and OpenCL to accelerate high-performance computing tasks, ensuring timely processing of large datasets and complex simulations.
REQUIRED QUALIFICATIONS
- Advanced proficiency in programming languages (Python for scripting and integration).
- Experience with CI/CD tools like GitHub Actions, Jfrog Artifactory, and Git.
- Proficiency with IaC tools (Terraform, Ansible).
- Experience with cloud platforms (Azure, AWS, GCP).
- Proficiency in containerization (Docker) and container orchestration (Kubernetes).
- Knowledge of model registries and feature stores (e.g., MLflow, Kubeflow).
- Experience with logging and monitoring tools (ELK Stack, Prometheus, Grafana).
- Understanding of parallel computing frameworks (CUDA, OpenCL).
- Strong collaboration skills and proficiency with collaborative tools (JIRA, Confluence).
- Eligible to obtain and maintain an active U.S. Secret security clearance.
PREFERRED QUALIFICATIONS
- Previous experience in a manufacturing or industrial setting.
- Familiarity with observability concepts and tools.
- Knowledge of security best practices for DevOps and MLOps.
The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. Highly competitive equity grants are included in the majority of full time offers; and are considered part of Anduril's total compensation package. Additionally, Anduril offers top-tier benefits for full-time employees, including:
Benefits
At Anduril, we invest in our people. Our comprehensive, competitive benefits package (available at little to no cost to employees) ensures you’re supported in health, recovery, and whatever comes next. For more information, Explore Our Benefits.
Protecting Yourself from Recruitment Scams
Anduril is committed to maintaining the integrity of our Talent acquisition process and the security of our candidates. We've observed a rise in sophisticated phishing and fraudulent schemes where individuals impersonate Anduril representatives, luring job seekers with false interviews or job offers. These scammers often attempt to extract payment or sensitive personal information.
To ensure your safety and help you navigate your job search with confidence, please keep the following critical points in mind:
-
No Financial Requests: Anduril will never solicit payment or demand personal financial details (such as banking information, credit card numbers, or social security numbers) at any stage of our hiring process. Our legitimate recruitment is entirely free for candidates.
- Please always verify communications:
- Direct from Anduril: If you receive an email from one of our recruiters, it will only come from an
@anduril.comaddress. - Via Agency Partner: If contacted by a recruiting agency for an Anduril role, their email will clearly identify their agency. If you suspect any suspicious activity, please verify the agency's authenticity by reaching out to contact@anduril.com.
- Direct from Anduril: If you receive an email from one of our recruiters, it will only come from an
-
Exercise Caution with Unsolicited Outreach: If you receive any communication that appears suspicious, contains grammatical errors, or makes unusual requests, do not engage. Always confirm the sender's email domain is @anduril.com before providing any personal information or clicking on links.
-
What to Do If You Suspect Fraud: Should you encounter any questionable or fraudulent outreach claiming to be from Anduril, please report it immediately to contact@anduril.com. Your proactive caution is invaluable in protecting your personal information and upholding the security and trustworthiness of our recruitment efforts.
Data Privacy
To view Anduril's candidate data privacy policy, please visit https://anduril.com/applicant-privacy-notice/.
By submitting your application, you consent to Anduril Industries using a third-party service provider to conduct pre-employment risk, integrity, and due diligence screening and assessing potential risks as part of your application process. This third-party service provider provides risk-intelligence services that may include analysis of sanctions and watchlists, adverse media, public-record information, and other lawful open-source or commercial data sources. This third-party service provider does not act as a consumer reporting agency. Use of this provider helps to ensure compliance with applicable laws and protect technology, intellectual property, and organizational security.
Ready to apply?
Apply to Anduril Industries
Senior Machine Learning/MLOps Engineer
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Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.
ABOUT THE TEAM
Anduril Maritime delivers platforms, systems, and integrated effects in the maritime domain. Our autonomous vehicles (sub-surface and surface) are the cornerstone of these capabilities, and we continually strive to push the boundaries of the possible in terms of endurance, autonomy and mission capability. The Maritime team develops and maintains core products and payloads, and adapts and applies those products to serve a wide variety of defense, IC and commercial customers in US and international markets.
ABOUT THE JOB
We are seeking a Senior Machine Learning/MLOps Engineer to join the Applied Intelligence team within Maritime Digital Production. You will lead the design, deployment, and sustainment of the AI-enabled backbone that connects data, tools, and people across our digital shipbuilding environment. This role focuses on operationalizing advanced models and architecting the industrial AI stack—selecting, integrating, and standardizing technologies that bring intelligence into production systems only where they deliver real value.
You’ll define and implement core components of the platform, including unified data and feature stores, vector databases, orchestration layers, and model-serving frameworks, while integrating off-the-shelf models for computer vision, OCR/IDP, speech, and retrieval-augmented generation. You’ll work across software, data, manufacturing, and corporate technology teams to translate real factory scenarios—inspection, root-cause analysis, receiving workflows, scheduling—into applied AI capabilities with clear human-in-the-loop controls, auditability, safety gates, and integrations with PLM, MES, CMMS, ERP, and the unified data plane.
This role demands technical range, judgment, and an instinct for when AI is the right tool versus when a simpler logic or workflow solution wins. You’ll collaborate across Anduril in a high-tech, fast-paced culture of innovation focused on delivering systems that work in the real world. If you want to shape how AI becomes a practical, reliable tool for production and logistics at scale, you’ll be helping build the future of digital shipbuilding and the next generation of maritime vehicles.
WHAT YOU’LL DO
- Architect and own the AI/ML platform stack—from data ingestion, labeling, and feature engineering to model training, deployment, monitoring, and lifecycle management.
- Select, prioritize, and standardize industrial AI components including feature stores, vector databases + RAG, OCR/IDP and CV/STT providers, orchestration layers, and observability systems.
- Build model-serving and inference frameworks optimized for production environments, supporting real-time and batch execution across cloud, edge, and shop-floor systems.
- Translate factory scenarios (receiving, inspection, RCCA, scheduling) into applied AI workflows with defined human-in-the-loop gates, audit trails, and integration contracts with PLM, MES, CMMS, ERP, and the unified data plane.
- Implement event-driven data pipelines and telemetry systems that feed models with contextualized, real-time signals from production and logistics systems.
- Drive make/buy strategy by researching internal and vendor AI capabilities and recommending investments aligned to enterprise roadmaps, Anduril IP principles, and production constraints.
- Define and maintain model governance processes for validation, safety reviews, traceability, and rollback.
- Partner with Maritime platform teams and CorpTech to align architectures with enterprise data standards, ontologies, and compliance policies.
- Lead reliability engineering for deployed models—managing drift detection, retraining triggers, alerting, and operational SLOs.
- Mentor junior engineers and data scientists; establish best practices for MLOps, observability, data management, and secure handling of sensitive production data.
REQUIRED QUALIFICATIONS
- Strong stakeholder management skills with proven experience aligning engineering, data, and manufacturing teams.
- 8+ years of experience in software or ML engineering with end-to-end delivery of production-grade AI/ML systems.
- Deep experience with MLOps: data acquisition, labeling, curation, pipeline management, model versioning, continuous integration, and model monitoring.
- Strong proficiency in Python and experience with deep learning frameworks (PyTorch, TensorFlow).
- Experience building and deploying containerized ML services using Docker and Kubernetes.
- Proficiency in data engineering, time-series data modeling, and working with semantic/ontology-driven data systems.
- Experience implementing observability for model performance, inference accuracy, and data drift.
- Familiarity with event-driven architectures, IoT/UNS patterns, and real-time systems integration.
- Excellent communication and documentation abilities; able to bridge research, platform, and production domains.
- Eligible to obtain and maintain an active U.S. Secret security clearance.
PREFERRED QUALIFICATIONS
- Experience applying AI/ML within manufacturing, logistics, industrial control, or production environments.
- Background with digital twins, predictive maintenance, OCR/IDP, CV, or STT model integrations.
- Experience with workflow/orchestration tools such as Flyte, Airflow, Kubeflow, or Temporal.
- Familiarity with GPU acceleration (CUDA) and inference optimization (TensorRT, Triton).
- Experience in regulated environments (NNPI/ITAR) and secure model/data governance.
- Demonstrated ability to mentor engineers and set technical direction for AI/ML infrastructure at scale.
The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. Highly competitive equity grants are included in the majority of full time offers; and are considered part of Anduril's total compensation package. Additionally, Anduril offers top-tier benefits for full-time employees, including:
Benefits
At Anduril, we invest in our people. Our comprehensive, competitive benefits package (available at little to no cost to employees) ensures you’re supported in health, recovery, and whatever comes next. For more information, Explore Our Benefits.
Protecting Yourself from Recruitment Scams
Anduril is committed to maintaining the integrity of our Talent acquisition process and the security of our candidates. We've observed a rise in sophisticated phishing and fraudulent schemes where individuals impersonate Anduril representatives, luring job seekers with false interviews or job offers. These scammers often attempt to extract payment or sensitive personal information.
To ensure your safety and help you navigate your job search with confidence, please keep the following critical points in mind:
-
No Financial Requests: Anduril will never solicit payment or demand personal financial details (such as banking information, credit card numbers, or social security numbers) at any stage of our hiring process. Our legitimate recruitment is entirely free for candidates.
- Please always verify communications:
- Direct from Anduril: If you receive an email from one of our recruiters, it will only come from an
@anduril.comaddress. - Via Agency Partner: If contacted by a recruiting agency for an Anduril role, their email will clearly identify their agency. If you suspect any suspicious activity, please verify the agency's authenticity by reaching out to contact@anduril.com.
- Direct from Anduril: If you receive an email from one of our recruiters, it will only come from an
-
Exercise Caution with Unsolicited Outreach: If you receive any communication that appears suspicious, contains grammatical errors, or makes unusual requests, do not engage. Always confirm the sender's email domain is @anduril.com before providing any personal information or clicking on links.
-
What to Do If You Suspect Fraud: Should you encounter any questionable or fraudulent outreach claiming to be from Anduril, please report it immediately to contact@anduril.com. Your proactive caution is invaluable in protecting your personal information and upholding the security and trustworthiness of our recruitment efforts.
Data Privacy
To view Anduril's candidate data privacy policy, please visit https://anduril.com/applicant-privacy-notice/.
By submitting your application, you consent to Anduril Industries using a third-party service provider to conduct pre-employment risk, integrity, and due diligence screening and assessing potential risks as part of your application process. This third-party service provider provides risk-intelligence services that may include analysis of sanctions and watchlists, adverse media, public-record information, and other lawful open-source or commercial data sources. This third-party service provider does not act as a consumer reporting agency. Use of this provider helps to ensure compliance with applicable laws and protect technology, intellectual property, and organizational security.
Ready to apply?
Apply to Anduril Industries
Staff Machine Learning Engineer, AI Research
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Join the company that’s building the telemetry infrastructure for the AI era. At Cribl, we partner with IT and Security teams at many of the world’s biggest enterprises, including half of the Fortune 100, to bridge the gap between AI ambition and infrastructure reality. As the AI Platform for Telemetry, we give customers the choice, control, and flexibility to manage and analyze telemetry for both humans and agents, so they can build what’s next.
We’re one of the fastest‑growing private companies and a leading player in a massive, fast‑moving market. With a global workforce, we’re remote‑first and grounded in a simple idea: software is a people business. Cribl is the place where curious, collaborative people can do their best work, grow fast, and bring their full selves to the herd.
Why You'll Love This Role
You will work closely with the founding team and a group of highly-skilled engineers to shape the future of AI-enabled Security/Observability platforms. You will play a central role in bringing integrating cutting-edge AI/ML technologies to the Cribl Product suite to help solve real customer problems. You will work closely with development partners and key stakeholders to iteratively design, develop, and deliver products and surfaces that will delight our customers.
On top of it all you will have fun. Cribl strives to be a great place to work for everyone.
As An Active Member Of Our Team, You Will...
- Design, train, and evaluate machine learning models across a range of research and applied AI initiatives
- Run rapid, iterative experiments to test hypotheses and surface insights that drive model improvements
- Collaborate closely with researchers and engineers to translate cutting-edge academic advances into practical, production-ready systems
- Build and maintain robust ML pipelines for data ingestion, feature engineering, model training, and evaluation
- Optimize model performance through fine-tuning, hyperparameter search, and architecture experimentation
- Contribute to a culture of rigorous experimentation; tracking results, documenting findings, and sharing learnings with the broader team
- Stay current with the latest developments in ML and AI research, and proactively identify opportunities to apply them
- This position may require stand-by, on-call, or off-hours duties during critical research or deployment milestones
If You've Got It - We Want It
- Bachelor's degree in Computer Science, Mathematics, Statistics, or a related field with 5+ years of industry or research experience (Master's or PhD a plus)
- Deep hands-on experience training and evaluating ML models, including language models
- Strong proficiency in Python and ML frameworks such as PyTorch or TensorFlow
- Familiarity with MLOps tooling and infrastructure (e.g., MLflow, Weights & Biases, Kubeflow, or similar)
- Solid understanding of modern NLP, computer vision, and/or reinforcement learning techniques
- Strong ability to move fast without sacrificing rigor; you know when to prototype and when to productionize
- Excellent communication skills with the ability to clearly present experimental results to both technical and non-technical stakeholders
Salary Range ($230,000 - $275,000)
The salary for this role is dependent on geographic location. The salary offered within the range described will be based on the individual candidate’s job-related knowledge, skills, and experience. In addition to a competitive salary, Cribl also offers a generous benefits package which includes health, dental, vision, short-term disability, and life insurance, paid holidays and paid time off, a fertility treatment benefit, 401(k), equity, and eligibility for a discretionary company-wide bonus.
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Bring Your Whole Self
Diversity drives innovation, enables better decisions to support our customers, and inspires change for the better. We’re building a culture where differences are valued and welcomed, and we work together to bring out the best in each other. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or any other applicable legally protected characteristics in the location in which the candidate is applying.
Interested in joining the Cribl herd? Learn more about the smartest, funniest, most passionate goats you’ll ever meet at cribl.io/about-us.
Ready to apply?
Apply to Cribl
Archer is an aerospace company based in San Jose, California building an all-electric vertical takeoff and landing aircraft with a mission to advance the benefits of sustainable air mobility. We are designing, manufacturing, and operating an all-electric aircraft that can carry four passengers while producing minimal noise.
Our sights are set high and our problems are hard, and we believe that diversity in the workplace is what makes us smarter, drives better insights, and will ultimately lift us all to success. We are dedicated to cultivating an equitable and inclusive environment that embraces our differences, and supports and celebrates all of our team members.
We are looking for a highly motivated and versatile Senior Platform Engineer to join our platform engineering team. This unique role is central to accelerating our product development lifecycle and operational efficiency. You will be instrumental in bridging the gap between development, infrastructure, and our burgeoning AI/ML initiatives, focusing on automation, self-service infrastructure, and workflow optimization. This position is ideal for an experienced engineer who thrives on creating leverage for others and tackling complex, interdisciplinary challenges.
Key Responsibilities:
CI/CD and Automation
- Design, implement, and maintain scalable and reliable CI/CD pipelines (e.g., using GitLab CI, GitHub Actions, Jenkins, Spinnaker) to ensure rapid and safe deployments across multiple environments.
- Drive the adoption of best practices for build management, testing automation, and deployment strategies (Canary, Blue/Green, etc.).
- Minimize deployment friction and cycle time for all engineering teams.
Self-Service Infrastructure & Provisioning
- Develop and champion self-service tooling and internal platforms (leveraging tools like Terraform, Ansible, Kubernetes, or equivalent cloud provider APIs) that empower development teams to provision and manage their own infrastructure resources securely and efficiently.
- Establish guardrails and policy-as-code to ensure compliance, cost efficiency, and security across all provisioned infrastructure.
AI Infrastructure Enhancement & Support
- Collaborate closely with AI/ML Engineers to improve the underlying platform used for model training, experimentation, and serving.
- Focus on the operationalization of MLOps pipelines, including data lineage tracking, feature store integration, and production model deployment automation.
- Assist in optimizing resource allocation (e.g., GPU usage, specialized hardware) for AI workloads.
Workflow Automation & Internal Tooling
- Architect and build automated workflows and bots, primarily within communication tools like Slack or Zoom, to streamline common engineering tasks (e.g., on-call handoffs, incident response, environment status checks, approval processes).
- Develop internal APIs and services that connect disparate engineering systems to enhance communication and cross-functional transparency.
Required Qualifications
- 5+ years of professional experience in Platform Engineering, DevOps, Site Reliability Engineering (SRE), or a related discipline.
- Deep expertise in cloud platforms (AWS, GCP, or Azure) and infrastructure-as-code tools (Terraform strongly preferred).
- Expertise in containerization and orchestration technologies (Docker and Kubernetes).
- Proficiency in scripting and general-purpose programming languages (e.g., Python, Go, Bash).
- Extensive experience designing and managing CI/CD systems at scale.
- Proven track record of building internal developer platforms or self-service tools.
Preferred Qualifications
- Experience with AI/ML infrastructure, MLOps tooling, or data pipeline technologies (e.g., Airflow, Kubeflow, Vertex AI, SageMaker).
- Prior experience building conversational interfaces, bots, or workflow automation tools for platforms like Slack or Teams.
- Familiarity with distributed tracing, logging, and monitoring systems (e.g., Prometheus, Grafana, ELK stack, Datadog).
- Experience with security best practices in a cloud environment (IAM, network security, secrets management).
At Archer we aim to attract, retain, and motivate talent that possess the skills and leadership necessary to grow our business. We drive a pay-for-performance culture and reward performance that supports the Company’s business strategy. For this position we are targeting a base pay between $144,000 - $175,000. Actual compensation offered will be determined by factors such as job-related knowledge, skills, and experience.
Archer is proud to be an Equal Opportunity employer committed to diversity and inclusivity in the workplace. All aspects of employment are decided on the basis of merit, qualifications, and business needs. We do not discriminate based upon race, color, religion, sex, sexual orientation, age, national origin, disability status, protected veteran status, gender identity or any other characteristic protected by federal, state or local laws.
Archer is committed to working with and providing reasonable accommodations to job applicants with physical or mental disabilities, and those with sincerely held religious beliefs. Applicants who may require reasonable accommodation for any part of the application or hiring process should provide their name and contact information to Archer’s People Team at people@archer.com. Reasonable accommodations will be determined on a case-by-case basis.
Information collected and processed as part of any job applications you choose to submit is subject to Archer's Candidate Privacy Policy.
Archer is unable to provide work visa sponsorship for this position at the present time.
Archer is proud to be an Equal Opportunity employer committed to diversity and inclusivity in the workplace. All aspects of employment are decided on the basis of merit, qualifications, and business needs. We do not discriminate based upon race, color, religion, sex, sexual orientation, age, national origin, disability status, protected veteran status, gender identity or any other characteristic protected by federal, state or local laws.
Archer Aviation does not engage with external recruiting agencies/individual recruiters with whom it does not have a prior written agreement. Archer reserves the right to make use of any unsolicited resumes that it receives and bears no responsibility for payment of any fees asserted from the use of unsolicited resumes. If you are a recruiting agency or individual recruiter wishing to do business with Archer, please reach out to People@archer.com. All employment processes are managed by the Archer People Team.
Ready to apply?
Apply to Archer
SmarterDx, a Smarter Technologies company, builds clinical AI that is transforming how hospitals translate care into payment. Founded by physicians in 2020, our platform connects clinical context with revenue intelligence, helping health systems recover millions in missed revenue, improve quality scores, and appeal every denial. Become a Smartian and help optimize the way the healthcare system works for everyone. Learn more at smarterdx.com/careers.
Role
SmarterDx is seeking a Manager of Data Engineering, Development to lead and grow a high-performing data engineering team responsible for building next-generation data pipeline capabilities, architecting scalable data solutions, and developing new data products to power our clinical AI applications. You will drive innovation in our data stack and data pipelines, establish technical best practices, and ensure robust, observable, and cost-effective data architectures. You will set clear objectives, mentor engineers, as well as partner closely with Product, Clinical, Data Science, and Software Engineering teams to deliver transformative data capabilities.
SmarterDx builds clinical AI that empowers hospitals to analyze the complete record of every patient to fully capture the value of care delivered. Founded by physicians in 2020, its proprietary AI platform understands the nuances of clinical reasoning, enabling hospitals to true the patient record for every discharge. By doing so, hospitals can recover millions in earned revenue, enhance care quality metrics, and optimize healthcare operations. Become a Smartian and help optimize the way the healthcare system works for everyone. Learn more at smarterdx.com/careers.
**This role is fully remote within the US**
What You'll Do
- Lead, coach, and develop a team of senior data engineers with a focus on technical innovation, platform capabilities, and engineering excellence.
- Contribute to the data engineering product roadmap by designing and implementing new data pipeline architectures, patterns, and reusable frameworks.
- Architect scalable data solutions using modern tooling (dbt, Airflow, Snowflake, AWS, Python) to enable advanced analytics and ML capabilities.
- Establish development standards and best practices including code reviews, testing frameworks, CI/CD pipelines, and documentation standards.
- Develop sophisticated data models and transformations using advanced dbt patterns (custom macros, packages, incremental models) to enhance our production pipelines
- Collaborate cross-functionally to help translate business requirements into technical solutions and drive innovation initiatives.
- Develop automated data quality frameworks, monitoring solutions, and observability tools to ensure data reliability at scale.
- Create developer productivity tools and accelerators that enable the team to deliver features faster with higher quality.
- Drive technical design reviews, architectural decisions, and technology evaluations to ensure platform scalability and maintainability.
What You Bring
- 7+ years of data engineering experience, including leadership of engineers and technical projects (architecture, design, delivery).
- Deep expertise with modern data stack: advanced dbt development, Snowflake optimization, Python, and SQL at scale.
- Strong expertise with AWS cloud architecture skills: hands-on experience in serverless and infrastructure-as-code patterns.
- Proven track record building and scaling data platforms that support analytics, ML, and product features.
- Developer excellence mindset with expertise in Git, CI/CD, testing, code reviews, and agile development practices.
- Demonstrated ability to drive technical innovation while balancing technical debt, performance optimization, and feature delivery.
- Excellent communication and technical leadership skills: comfortable driving architectural decisions and mentoring senior engineers.
- Experience in healthcare datasets with understanding of the inherent contextual and relational complexities within healthcare data.
Nice To Haves
- Experience at a scale-up or rapid-growth technology company.
- Advanced Snowflake features expertise (streams, tasks, dynamic tables, data sharing).
- Infrastructure-as-code proficiency (AWS CDK, CloudFormation, Terraform).
- ML engineering experience: feature stores, model deployment, MLOps practices.
- Healthcare interoperability knowledge (HL7, FHIR, CCD/C-CDA).
- Certifications: Snowflake (SnowPro Advanced), AWS (Data Analytics or Solutions Architect Professional), dbt, or healthcare data (CHDA/RHIA).
- Experience building data mesh architectures or domain-driven data platforms.
Our Tech Stack
- Databases: Snowflake (primary), Postgres
- Cloud Infrastructure: AWS (CDK, S3, MWAA, EventBridge, Batch, Lambda, Step Functions), FiveTran
- Technologies: SQL, dbt, Python
Compensation
$190,000 - $220,000
#LI-Remote
Benefits
- Medical, Dental & Vision – Comprehensive plans with leading insurance providers, covering 75% of your premiums, depending on the plan.
- Paid Parental Leave – Generous paid leave to support families through birth or adoption: Up to 12 weeks for parents.
- Remote-First Team – Work from anywhere in the U.S.
- Unlimited PTO & 10 Holidays – So you can relax and recharge.
- 401(k) with Traditional & Roth Options – Tax-advantaged retirement savings through Fidelity with a 4% match.
- Minimal Bureaucracy – A fast-moving, high-impact environment where you can focus on what matters.
- Incredible Teammates! – Work alongside smart, supportive, and mission-driven colleagues.
Ready to apply?
Apply to SmarterDxSmarterDx, a Smarter Technologies company, builds clinical AI that is transforming how hospitals translate care into payment. Founded by physicians in 2020, our platform connects clinical context with revenue intelligence, helping health systems recover millions in missed revenue, improve quality scores, and appeal every denial. Become a Smartian and help optimize the way the healthcare system works for everyone. Learn more at smarterdx.com/careers.
Role
As Director of Data Science at SmarterDx, you will own the direction and impact of data science across multiple product areas within our Clinical AI platform at a moment of rapid product and company growth. You will translate company strategy into clear priorities and lead teams responsible for production machine learning systems that directly shape clinical workflows and business outcomes.
This role blends technical and people leadership with close partnership across Product, Engineering, and Clinical teams. You will set modeling and quality standards, develop managers and senior individual contributors, and guide machine learning systems from concept through responsible deployment in real healthcare environments, building reliable systems and teams that customers and clinicians depend on.
**This role is fully remote within the US**
What You’ll Do
- Own and evolve the Data Science strategy across multiple product areas, translating company and product objectives into a clear, prioritized roadmap with measurable business impact.
- Drive portfolio-level prioritization, balancing near-term delivery with longer-term platform and capability investments.
- Set technical direction and standards for production ML systems, with end-to-end ownership from problem framing and data strategy through deployment, monitoring, and iteration.
- Partner closely with Product, Engineering, Clinical, and Operations leaders to embed data science into product workflows and decision-making.
- Represent Data Science in product planning and executive forums, communicating tradeoffs, risks, and impact to senior stakeholders.
- Lead and scale the Data Science organization, including managers, senior ICs, and emerging leaders, with clear expectations and ownership.
- Own hiring, onboarding, and talent development, building durable career paths and a high-performing organization.
- Champion responsible, interpretable, and clinically sound AI, ensuring models are appropriate for healthcare use and real-world deployment.
What You Bring
- 10+ years of experience in data science, machine learning, or a related field, including significant people leadership responsibility.
- Proven experience owning outcomes across multiple teams or product areas.
- Track record of influencing executive stakeholders and shaping company strategy.
- Deep expertise in machine learning fundamentals, with demonstrated ability to architect ML systems and set technical direction for senior teams.
- Experience with NLP and healthcare data, including structured and unstructured clinical text.
- Deep understanding of model evaluation, monitoring, experimentation, and real-world feedback loops.
- Familiarity with modern ML platforms, cloud infrastructure, and MLOps best practices.
- Demonstrated ability to connect technical work to revenue, margin, and customer outcomes.
- Exceptional communication skills, with the ability to translate complex technical concepts for non-technical audiences.
- Strong judgment in balancing speed, rigor, and long-term scalability.
Nice To Haves
- Prior experience leading Data Science at a high-growth startup.
- Experience with revenue cycle management or hospital operations.
- Knowledge of explainable AI and regulatory considerations in healthcare.
- Experience building or scaling ML platforms used by multiple teams.
- Experience leveraging Large Language Models (LLMs) in production systems.
Our Tech Stack
- Python
- SQL
- PyTorch
- SageMaker
- Snowflake
Compensation
$260k to 280k base + equity incentives
#LI-Remote
Benefits
- Medical, Dental & Vision – Comprehensive plans with leading insurance providers, covering 75% of your premiums, depending on the plan.
- Paid Parental Leave – Generous paid leave to support families through birth or adoption: Up to 12 weeks for parents.
- Remote-First Team – Work from anywhere in the U.S.
- Unlimited PTO & 10 Holidays – So you can relax and recharge.
- 401(k) with Traditional & Roth Options – Tax-advantaged retirement savings through Fidelity with a 4% match.
- Minimal Bureaucracy – A fast-moving, high-impact environment where you can focus on what matters.
- Incredible Teammates! – Work alongside smart, supportive, and mission-driven colleagues.
Ready to apply?
Apply to SmarterDxSmarterDx, a Smarter Technologies company, builds clinical AI that is transforming how hospitals translate care into payment. Founded by physicians in 2020, our platform connects clinical context with revenue intelligence, helping health systems recover millions in missed revenue, improve quality scores, and appeal every denial. Become a Smartian and help optimize the way the healthcare system works for everyone. Learn more at smarterdx.com/careers.
Role
As a Senior Data Scientist at SmarterDx, you will play a pivotal role in training cutting-edge machine learning models and ensuring their strategic integration into our Clinical AI Platform. Your work will focus on maximizing the business impact of deployed models by optimizing business logic, refining decision frameworks, and accelerating the end-to-end process of model development and deployment. You will collaborate closely with cross-functional teams to enhance our models’ clinical intelligence and delight our customers. This is a high-impact role ideal for someone who thrives in a fast-paced environment and is eager to see their work translate into tangible business outcomes.
**This role is fully remote within the US**
What You’ll Do
- Develop and refine modeling approaches in close collaboration with the Machine Learning Research team, iterating on experiments to improve model performance.
- Execute rapid experimentation cycles, documenting learnings and identifying promising avenues for further development.
- Support deployment efforts by creating standardized model endpoints and interfaces for seamless integration with product workflows.
- Contribute to shared modeling infrastructure, building tools and utilities that accelerate experimentation and standardize workflows across teams.
- Collaborate with Engineering, Analytics, and Product teams to integrate machine learning models into product workflows, ensuring they drive measurable business KPIs.
- Adapt and enhance existing modeling approaches to drive impact in new product areas.
- Identify product needs and communicate them effectively across the Data Science and Machine Learning Research Science teams.
What You Bring
- 3+ years of experience in data science, machine learning, or a related field, preferably in a product-driven environment.
- Strong proficiency in Python and hands-on experience with deep learning frameworks (PyTorch, TensorFlow)
- Deep understanding of statistical modeling, optimization techniques, and data analysis.
- Experience working with structured and text data, including feature engineering and data preprocessing.
- Ability to translate business objectives into data science problems and effectively communicate results to stakeholders.
- Experience deploying machine learning models into production and optimizing model performance based on real-world feedback.
- Strong collaboration skills and the ability to work across cross-functional teams including Engineering, Product, and Analytics.
- Familiarity with cloud platforms (AWS, GCP, or Azure) and MLOps best practices.
- A problem-solving mindset with the ability to balance technical rigor with practical business impact.
Nice To Haves
- Experience in healthcare or revenue cycle management.
- Familiarity working with large-scale data warehouses such as Snowflake.
- Experience building internal tools or infrastructure to support machine learning experimentation and deployment.
- Previous experience working in a startup or high-growth environment.
- Knowledge of explainable AI techniques and model interpretability best practices.
- Experience developing products leveraging Large Language Models (LLMs).
Our Tech Stack
- Python
- SQL
- PyTorch
- Sagemaker
- Snowflake
Compensation
$190 to 220k base
#LI-Remote
#LI-DNP
Benefits
- Medical, Dental & Vision – Comprehensive plans with leading insurance providers, covering 75% of your premiums, depending on the plan.
- Paid Parental Leave – Generous paid leave to support families through birth or adoption: Up to 12 weeks for parents.
- Remote-First Team – Work from anywhere in the U.S.
- Unlimited PTO & 10 Holidays – So you can relax and recharge.
- 401(k) with Traditional & Roth Options – Tax-advantaged retirement savings through Fidelity with a 4% match.
- Minimal Bureaucracy – A fast-moving, high-impact environment where you can focus on what matters.
- Incredible Teammates! – Work alongside smart, supportive, and mission-driven colleagues.
Ready to apply?
Apply to SmarterDx