MLOps Jobs in San Francisco.
All active MLOps roles based in San Francisco.
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About Arize
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 a client-obsessed AI Solutions Engineer with entrepreneurial tendencies to join the good fight and help build out our Solutions Engineering org. You’ll be the trusted technical advisors for our customers, driving business value, offering advice, and growing accounts. You’ll accomplish this by leading customers to solutions oftentimes by teaching the product to new users or consulting on best practices. You must be ready for technical discussions with data scientists and engineers, then demonstrate the value of Arize in business discussions with directors and executives. The goal is to enable our customers to become successful and enthusiastic about Arize. While we are a remote-first company, the nature of this role requires candidates to be based in the San Francisco Bay area/PST time zone.
What You’ll Do
- Work closely with some of the most sophisticated ML / GenAI teams in the world.
- You will act as a trusted advisor to our customers, while also building relationships with technical and business stakeholders.
- Advise on GenAI and ML best practices
- Give ML and LLM product demos to technical and business stakeholders
- Run strategic business reviews for customers in partnership with our sales team
- Interface with our pre-sales engineering team to gather client goals and KPI’s.
- Partner with our product and engineering teams to help drive the product roadmap
- Spearhead new opportunities within existing accounts to help drive expansions.
What We’re Looking For
Note: Even if you do not check every single box, we still encourage you to apply!
- Previous experience working as a Data Scientist, Machine Learning Engineer, or as an Engineer working with ML models or GenAI applications in production.
- Comfortable working in public Cloud environments (AWS, Azure, GCP)
- Knowledge of machine learning frameworks such as TensorFlow, PyTorch or Scikit-learn
- Knowledge of LLM / Agentic frameworks such as Llamaindex, LangGraph, and DSPy
- Understanding of ML/DS concepts, model evaluation strategies and lifecycle (feature generation, model training, model deployment, batch and real time scoring via REST APIs) and engineering considerations
- Understanding of GenAI concepts and application evaluation + development lifecycle
- Proficiency in a programming language (Python, JS/TS, Java, Go, etc)
- Strong Communication Skills - Ability to simplify complex, technical concepts.
- A quick and self learner - undaunted by technical complexity of production ML deployments and welcome the challenge to learn about them and develop your own POV.
Bonus Points, But Not Required
- Previous engineering experience in:
- Data Science
- MLOps
- ML Frameworks
- LLM / Agentic frameworks
- Customer facing experience strongly preferred such as Solutions Architect, Implementation Specialist, Sales Engineer, Customer Success Engineer, Consultant, or Professional Service roles
- Prior experience working with applications deployed with Kubernetes
- Prior experience demoing technical products to both business and technical audiences
The estimated annual salary and variable compensation for this role is between $125,000 - $175,000, 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
Ready to apply?
Apply to Arize AI
Staff Machine Learning Platform Engineer
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About Faire
Faire is a technology wholesale platform built on the belief that the future is local. Independent retailers around the globe collectively represent a multi-hundred-billion-dollar wholesale market that has historically been fragmented and offline. At Faire, we're using the power of tech, data, and machine learning to connect this thriving community of entrepreneurs across the globe. Picture your favorite boutique in town — we help them discover the best products from around the world to sell in their stores. With the right tools and insights, we believe that we can level the playing field so businesses can grow and local communities can thrive.
We’re looking for smart, resourceful and passionate people to join us as we power the shop local movement. If you believe in community, come join ours.
About this role
As a Staff Machine Learning Platform Engineer, you will help design, improve, and operate a scalable ML platform to accelerate model training, deployment, and governance. You are the technical bridge between data science and production engineering. You’ll be joining a small but deeply critical team that scales Faire’s ability to support tens of thousands of local businesses in a constantly narrowing retail landscape.
What You Will Do
- Design and operate ML infrastructure, including workspaces, clusters, jobs, and workflows
- Productionize ML workloads using Spark, Delta Lake, MLflow, and Databricks Workflows
- Teach data scientists how to utilize our ML platform to advance development from notebook to production for our most critical models
- Implement Unity Catalog for data governance, lineage, access control, and secure multi-tenant usage
- Build CI/CD pipelines for ML using Terraform and Git-based workflows (e.g., GitHub Actions)
- Optimize performance, reliability, and cost across training and inference workloads
- Configure Identity and Access Management (IAM) and Role Based Authentication Controls (RBAC) for sensitive data sets
- Establish observability for data quality, model performance, and platform health
- Build and maintain ML Platform technical documentation
What it takes
- 8+ years of experience building production ML or data platforms
- A degree (preferably graduate level) in Computer Science, Engineering, Statistics, or a related technical field
- Strong hands-on expertise with Databricks, Spark, Delta Lake, and MLflow.
- Proficiency in Python, SQL, and distributed systems concepts
- Experience with cloud platforms and infrastructure-as-code
- Solid understanding of MLOps best practices: CI/CD, monitoring, reproducibility, and security
- Experience supporting multiple ML teams in a shared platform environment
- Are an active owner of orphaned problems and are willing to assimilate whatever knowledge you’re missing to get the job done
Tech Stack
Faire uses a modern cloud based tech stack. For this role, you’ll want to be proficient with the following:
|
Category |
Technologies |
|
Languages |
Python, SQL, Kotlin |
|
ML Frameworks |
PyTorch, MLFlow |
|
Big Data & Processing |
Spark, Kafka, Databricks, Snowflake, Fivetran, Iceberg, Unity Catalog, Datadog, Airflow, Cockroach DB, MySQL |
|
Cloud & Infrastructure |
AWS, S3, SageMaker, Kubernetes, Docker, GitHub Actions, Terraform |
|
Generative AI |
Claude Sonnet 4.5, ChatGPT 5.2 |
Salary Range
Canada: the pay range for this role is $216,000 to $297,000 per year.
This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.
Faire uses Artificial Intelligence (AI) to screen and select applicants for this position.
This job posting is for an existing vacancy.
Hybrid Faire employees currently go into the office 3 days per week on Tuesdays, Thursdays, and a third flex day of their choosing (Monday, Wednesday, or Friday). Additionally, hybrid in-office roles will have the flexibility to work remotely up to 4 weeks per year. Specific Workplace and Information Technology positions may require onsite attendance 5 days per week as will be indicated in the job posting.
Why you’ll love working at Faire
- Move fast: You'll own meaningful problems that serve customers around the globe with the agency to move fast and see your results clearly.
- Equipped to scale: We invest in what matters, including the latest enterprise AI tools, to help you work smarter and get more out of every day.
- Best in class: Our team is full of sharp, kind, and generous colleagues who care about their craft and about helping you grow in yours.
- Real rewards. Competitive pay, equity, and comprehensive benefits designed to support your life inside and outside of work.
- Belonging: We're intentional about building an environment where every Faire employee has equal access to opportunities, growth, and success.
Faire was founded in 2017 by a team of early product and engineering leads from Square. We’re backed by some of the top investors in retail and tech including: Y Combinator, Lightspeed Venture Partners, Forerunner Ventures, Khosla Ventures, Sequoia Capital, Founders Fund, and DST Global. We have headquarters in San Francisco and Kitchener-Waterloo, and a global employee presence across offices in Toronto, London, and New York. To learn more about Faire and our customers, you can read more on our blog.
Faire provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity or gender expression.
Faire is committed to providing access, equal opportunity and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities. Accommodations are available throughout the recruitment process and applicants with a disability may request to be accommodated throughout the recruitment process. We will work with all applicants to accommodate their individual accessibility needs. To request reasonable accommodation, please fill out our Accommodation Request Form (https://bit.ly/faire-form)
Privacy
For information about the type of personal data Faire collects from applicants, as well as your choices regarding the data collected about you, please visit Faire’s Privacy Notice (https://www.faire.com/privacy)
Ready to apply?
Apply to Faire
About Faire
Faire is a technology wholesale platform built on the belief that the future is local. Independent retailers around the globe collectively represent a multi-hundred-billion-dollar wholesale market that has historically been fragmented and offline. At Faire, we're using the power of tech, data, and machine learning to connect this thriving community of entrepreneurs across the globe. Picture your favorite boutique in town — we help them discover the best products from around the world to sell in their stores. With the right tools and insights, we believe that we can level the playing field so businesses can grow and local communities can thrive.
We’re looking for smart, resourceful and passionate people to join us as we power the shop local movement. If you believe in community, come join ours.
About this role
As a Staff Machine Learning Platform Engineer, you will help design, improve, and operate a scalable ML platform to accelerate model training, deployment, and governance. You are the technical bridge between data science and production engineering. You’ll be joining a small but deeply critical team that scales Faire’s ability to support tens of thousands of local businesses in a constantly narrowing retail landscape.
What You Will Do
- Design and operate ML infrastructure, including workspaces, clusters, jobs, and workflows
- Productionize ML workloads using Spark, Delta Lake, MLflow, and Databricks Workflows
- Teach data scientists how to utilize our ML platform to advance development from notebook to production for our most critical models
- Implement Unity Catalog for data governance, lineage, access control, and secure multi-tenant usage
- Build CI/CD pipelines for ML using Terraform and Git-based workflows (e.g., GitHub Actions)
- Optimize performance, reliability, and cost across training and inference workloads
- Configure Identity and Access Management (IAM) and Role Based Authentication Controls (RBAC) for sensitive data sets
- Establish observability for data quality, model performance, and platform health
- Build and maintain ML Platform technical documentation
What it takes
- 8+ years of experience building production ML or data platforms
- A degree (preferably graduate level) in Computer Science, Engineering, Statistics, or a related technical field
- Strong hands-on expertise with Databricks, Spark, Delta Lake, and MLflow.
- Proficiency in Python, SQL, and distributed systems concepts
- Experience with cloud platforms and infrastructure-as-code
- Solid understanding of MLOps best practices: CI/CD, monitoring, reproducibility, and security
- Experience supporting multiple ML teams in a shared platform environment
- Are an active owner of orphaned problems and are willing to assimilate whatever knowledge you’re missing to get the job done
Tech Stack
Faire uses a modern cloud based tech stack. For this role, you’ll want to be proficient with the following:
|
Category |
Technologies |
|
Languages |
Python, SQL, Kotlin |
|
ML Frameworks |
PyTorch, MLFlow |
|
Big Data & Processing |
Spark, Kafka, Databricks, Snowflake, Fivetran, Iceberg, Unity Catalog, Datadog, Airflow, Cockroach DB, MySQL |
|
Cloud & Infrastructure |
AWS, S3, SageMaker, Kubernetes, Docker, GitHub Actions, Terraform |
|
Generative AI |
Claude Sonnet 4.5, ChatGPT 5.2 |
Salary Range
San Francisco: the pay range for this role is $246,500 to $339,000 per year.
This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.
Hybrid Faire employees currently go into the office 3 days per week on Tuesdays, Thursdays, and a third flex day of their choosing (Monday, Wednesday, or Friday). Additionally, hybrid in-office roles will have the flexibility to work remotely up to 4 weeks per year. Specific Workplace and Information Technology positions may require onsite attendance 5 days per week as will be indicated in the job posting.
Why you’ll love working at Faire
- Move fast: You'll own meaningful problems that serve customers around the globe with the agency to move fast and see your results clearly.
- Equipped to scale: We invest in what matters, including the latest enterprise AI tools, to help you work smarter and get more out of every day.
- Best in class: Our team is full of sharp, kind, and generous colleagues who care about their craft and about helping you grow in yours.
- Real rewards. Competitive pay, equity, and comprehensive benefits designed to support your life inside and outside of work.
- Belonging: We're intentional about building an environment where every Faire employee has equal access to opportunities, growth, and success.
Faire was founded in 2017 by a team of early product and engineering leads from Square. We’re backed by some of the top investors in retail and tech including: Y Combinator, Lightspeed Venture Partners, Forerunner Ventures, Khosla Ventures, Sequoia Capital, Founders Fund, and DST Global. We have headquarters in San Francisco and Kitchener-Waterloo, and a global employee presence across offices in Toronto, London, and New York. To learn more about Faire and our customers, you can read more on our blog.
Faire provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity or gender expression.
Faire is committed to providing access, equal opportunity and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities. Accommodations are available throughout the recruitment process and applicants with a disability may request to be accommodated throughout the recruitment process. We will work with all applicants to accommodate their individual accessibility needs. To request reasonable accommodation, please fill out our Accommodation Request Form (https://bit.ly/faire-form)
Privacy
For information about the type of personal data Faire collects from applicants, as well as your choices regarding the data collected about you, please visit Faire’s Privacy Notice (https://www.faire.com/privacy)
Ready to apply?
Apply to Faire
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.
Ready to apply?
Apply to Databricks
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
Senior Data Engineer - Data & ML Platform
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Our mission at Oura is to empower every person to own their inner potential. Our award-winning products help our global community gain a deeper knowledge of their readiness, activity, and sleep quality by using their Oura Ring and its connected app. We've helped millions of people understand and improve their health by providing daily insights and practical steps to inspire healthy lifestyles.
Empowering the world starts with living our values and empowering our team. As a quickly growing company focused on helping people live healthier and happier lives, we ensure that our team members have what they need to do their best work — both in and out of the office.
We are looking for a Senior Data Engineer to join our Data & ML Platform team, responsible for development, maintenance and support for Oura’s Datalake and adjacent systems, collaborating closely with data scientists, analysts and other departments utilizing the Datalake.
This is a hybrid role based in San Francisco, CA, working onsite 1-2 days per week.
We have offices in San Francisco, San Diego and Los Angeles for those who prefer hybrid or office settings. Oura employees in other major cities (like Boston and New York) occasionally gather informally at local co-working locations.
What you will do:
- Build, operate, and improve Oura’s Datalake consisting of systems to move, process, and store large amounts of data (Terabyte–Petabyte scale) leveraging tools such as AWS Kinesis, S3, Spark / Glue, Athena, dbt, Iceberg, Snowflake, Docker, workflow engines, and more.
- Design and implement data models and pipelines with a strong focus on data quality, reliability, and governance.
- Ensure that our data platform and processes meet privacy, compliance, and security requirements.
- Build components that support the handling of datasets, training, testing, and release of new on-device and cloud-based ML models.
- Independently collaborate with different stakeholders including Data Scientists, Testing, Firmware, and Hardware to define and implement improvements and new functionality and support internal Datalake consumers in their day-to-day work.
- Write code, mostly in Python and SQL with occasional additions Typescript, Java or some other language.
We would love to have you on our team if you have:
- 5+ years of experience developing and operating production systems.
- Experience running, monitoring, and debugging production systems at scale on a public cloud. We rely on AWS but experience with other cloud platforms counts too.
- Good architectural understanding of event-driven architectures, workflow engines, database, and data warehouse systems.
- Ability to design robust data models and pipelines, with attention to data accuracy and integrity.
- Experience in building infrastructure and components following best practices such as CI/CD and infrastructure as code.
- Demonstrated skills in writing well-structured, testable, and high-performance code.
- Familiarity with some of the following: Workflow engines, Stream processing, MLops, Spark, Athena, SQL, dbt, Databricks.
- You are self-motivated, proactive, and able to lead and manage your own work effectively.
- A pragmatic and goal oriented approach to development.
What Makes You Stand Out
- Real-life experience with Databricks.
- Familiarity and experience with the Data Mesh approach
- Broad knowledge of software fundamentals, databases, warehouses, and system design with experience on various programming languages
Benefits
At Oura, we care about you and your well-being. Everyone here at Oura has a ring of their own and we are continually looking to improve employee health.
What we offer:
- Competitive salary and equity packages
- Health, dental, vision insurance, and mental health resources
- An Oura Ring of your own plus employee discounts for friends & family
- 20 days of paid time off plus 13 paid holidays plus 8 days of flexible wellness time off
- Paid sick leave and parental leave
Oura takes a market-based approach to pay, which may vary depending on your location. US locations are categorized into tiers based on a cost of labor index for that geographic area. While most offers will be closer to the starting range, successful candidates' pay will be determined based on job-related skills, experience, qualifications, work location, internal peer equity, and market conditions. These ranges may be modified in the future.
- Region 1 $172,550 - $203,000
- Region 2 $159,000 - $187,000
- Region 3 $148,000 - $174,000
A recruiter can determine your zones/tiers based on your US location.
Oura is proud to be an equal opportunity workplace. We celebrate diversity and are committed to creating an inclusive environment for all employees. Individuals seeking employment at Oura are considered without regard to age, ancestry, color, gender (including pregnancy, childbirth, or related medical conditions), gender identity or expression, genetic information, marital status, medical condition, mental or physical disability, national origin, protected family care or medical leave status, race, religion (including beliefs and practices or the absence thereof), sexual orientation, military or veteran status, or any other characteristic protected by federal, state, or local laws. We will not tolerate discrimination or harassment based on any of these characteristics.
We will work to ensure individuals with disabilities are provided reasonable accommodation to participate in the interview process, to perform essential job functions, and to receive other benefits and privileges of employment.
Disclaimer: Beware of fake job offers!
We’ve been alerted to scammers posing as ŌURA recruiters, especially for remote roles. Please note:
- Our jobs are listed only on the ŌURA Careers page and trusted job boards.
- We will never ask for personal information like ID or payment for equipment upfront.
- Official offers are sent through Docusign after a verbal offer, not via text or email.
Stay cautious and protect your personal details.
To all recruitment agencies: Oura does not accept agency resumes. Please do not forward resumes to our jobs alias, Oura employees, or any other organization's location. Oura is not responsible for any fees related to unsolicited resumes.
Ready to apply?
Apply to Ōura
Heartflow is a medical technology company advancing the diagnosis and management of coronary artery disease, the #1 cause of death worldwide, using cutting-edge technology. The flagship product—an AI-driven, non-invasive cardiac test supported by the ACC/AHA Chest Pain Guidelines called the Heartflow FFRCT Analysis—provides a color-coded, 3D model of a patient’s coronary arteries indicating the impact blockages have on blood flow to the heart. Heartflow is the first AI-driven non-invasive integrated heart care solution across the CCTA pathway that helps clinicians identify stenoses in the coronary arteries (RoadMap™Analysis), assess coronary blood flow (FFRCT Analysis), and characterize and quantify coronary atherosclerosis (Plaque Analysis). Our pipeline of products is growing and so is our team; join us in helping to revolutionize precision heartcare.
Heartflow is a publicly traded company (HTFL) that has received international recognition for exceptional strides in healthcare innovation, is supported by medical societies around the world, cleared for use in the US, UK, Europe, Japan and Canada, and has been used for more than 500,000 patients worldwide.
We are seeking a high-impact Staff Data Scientist to play a leading role on our data needs to bridge the gap between advanced research and production-grade ML systems. You will be a key technical leader and partner to our Research Scientists, driving the evolution of our AI algorithms through rigorous data science methodologies, strategic data curation, and cross-functional leadership.
Job Responsibilities:
- Vision & Cross-Functional Leadership: Engage with cross-functional teams (Product, Research, Engineering, and Process Engineering) and help guide the overarching vision for data analysis, curation, and annotation to improve our AI models. Drive the definition of algorithm and data requirements necessary to deliver on end-point objectives.
- Data Campaigns and Annotation Strategy: Introduce best practices and efficient processes to enable multiple, large-scale annotation campaigns for continuous AI product improvements. Spearhead the strategic design of data campaigns needed to advance AI algorithms.
- Advanced Data Curation & Management: Develop comprehensive data curation strategies for improvements to AI models. Partner with MLOps to architect data management systems for algorithm training and performance validation, and establish data dashboards and monitoring reports.
- Performance Evaluation and Statistical Analysis: Establish frameworks and develop tools to rigorously evaluate the strengths and weaknesses of model iterations across patient populations. Design and oversee data analyses using statistical techniques to illuminate the performance of our AI algorithms.
Required Qualifications:
- Education: Masters or PhD Degree in Engineering, Computer Science, Statistics, Data Science or related degree.
- Work Experience: 7+ years (or 5+ with PhD) of proven track record in Data Science, Machine Learning, Computer Vision, or Image Analysis in industry. Have a wealth of experience from working on complex, real-world AI problems in medical imaging or computer vision requiring careful consideration of data needs.
- Software: Proficient in Python, including statistical and machine learning packages (e.g. scipy, sklearn, statsmodels, seaborn) with a commitment to writing clean, reproducible and scalable code. Familiarity with image and 3D processing tools like VTK and ITK, and visualization tools like 3DSlicer and MITK, a plus.
- Statistics: Understanding of standard statistical techniques and ability to apply appropriate statistical methods to a range of data structures; experience with medical imaging data a plus.
- Data Management: Experience working with data lakes, SQL/No SQL Databases, AWS Cloud Storage, Tableau dashboards.
- AI & Medical Imaging: Expertise in deep learning and machine learning models in production. Strong experience working with medical imaging data (CT and vascular imaging) is highly preferred.
- (Preferred) Proficiency in Agentic AI Tools: Experience integrating generative AI and agentic tools into daily workflows to act as a force multiplier—accelerating coding, prototyping, and complex data analysis—while demonstrating the critical judgment required to rigorously evaluate AI outputs for accuracy.
- Communication: Excellent written and verbal communication. Detail orientated but able to describe complex topics in a manner that is digestible to a broad audience. Ability to distill complex analyses into interpretable and actionable findings.
- Commitment: Committed to the success of the team and successful completion of project - 75% confidence / 100% committed.
- Influence without Authority: Able to build trust and obtain cross-functional alignment across departments.
A reasonable estimate of the base salary compensation range is $220,000 to $280,000, bonus, and equity. #LI-IB1 #LI-Hybrid
Ready to apply?
Apply to HeartflowLocation: San Francisco, CA (Hybrid)
What is Verse?
Energy markets are more volatile than ever. Rapid electrification and the rise of AI are driving unprecedented demand for power, while energy costs continue to rise across the globe. For the world’s largest energy buyers, managing energy has never been more complex or more critical.
Verse helps these organizations manage complex power portfolios with confidence by unifying energy data, planning, forecasting, and operations in one tool. Our Energy Cost Intelligence platform, Aria, brings together energy, finance, and operations teams with real-time, finance-ready intelligence—replacing spreadsheets and consultants with precision across the entire energy lifecycle. Built by an expert team of energy buyers, data scientists, and engineers, Verse enables faster, smarter energy decisions that reduce risk and lower energy costs.
The Role
Verse is seeking a Data Scientist to join our Data Science Team. In this role, you will lead the development and deployment of advanced data-driven solutions across a range of applications, including electricity markets, renewable procurement, and energy risk management. You will shape the machine learning and data modeling foundations that Verse's software is built on. For example, you might spend a cycle deploying electricity market price forecasting pipelines for new regions, developing solar production anomaly detection models, or creating scalable tools for benchmarking energy project financial performance.
Key Responsibilities
- Lead End-to-End Data Science Projects: Own and drive projects from problem definition through scoping, modeling, validation, and production deployment. Translate business problems into scalable, high-impact modeling solutions.
- Statistical & Machine Learning Modeling: Design, develop, and refine statistical and machine learning models (e.g., time series forecasting, probabilistic models) to support decision-making and enhance product capabilities.
- Analytics Engineering & Data Modeling: Perform complex data transformations and develop well-structured data models. Translate business and analytical requirements into scalable, tested, and well-documented datasets.
- Software Development & Productionization: Write clean, efficient, and maintainable Python code. Contribute to integrating models into production systems in a cloud-based environment while leveraging AI coding tools to accelerate development.
- MLOps: Contribute to Verse’s machine learning modeling infrastructure to support scaling of ML models and improving reliability, monitoring, and performance in production.
- Cross-Functional Collaboration: Partner with product, engineering, and business stakeholders to ensure models and insights are aligned with user needs and effectively integrated into workflows.
What We're Looking For (Minimum Qualifications)
- Master’s degree in Computer Science, Statistics, Engineering, Applied Mathematics, or a related quantitative field and 2+ years of professional experience in data science or machine learning; or
- Bachelor’s degree and 4+ years of professional experience in data science or machine learning
- Strong foundation in statistical modeling and machine learning, including time series forecasting and model evaluation
- Experience deploying and maintaining models in cloud-based environments (e.g., AWS, GCP, or Azure) using MLOps practices
- Strong Python expertise, including experience with scientific computing and ML libraries (e.g., NumPy, pandas, scikit-learn, PyTorch, TensorFlow)
- Hands-on experience in orchestrating complex data transformations (e.g. Airflow, Dagster, dbt)
- Strong software engineering practices (version control, testing, code reviews, CI/CD)
- Strong communication skills, with the ability to explain technical concepts to non-technical stakeholders
What Will Make You Standout (Preferred Qualifications)
- Experience in energy, climate tech, or related domains (not required)
- Familiarity with optimization methods or operations research
- Experience developing probabilistic forecasting models and quantifying uncertainty
- PhD in a quantitative field
What Makes Verse a Great Place to Work?
- Lead with Empathy: We lift each other up with humility and kindness, always putting colleagues and customers first
- Be Honest & Transparent: We prioritize effective communication to build trust with our team, customers, and stakeholders
- Move with Balance & Precision: We believe speed and perseverance must be accompanied by thoughtfulness and reflection
- Leave the World a Better Place: We are passionate about our mission, and we strive to create a sustainable world for future generations
Base Pay Range
$146,000 - $172,000
This is the estimated base salary range for this position, which does not include the value of benefits or a potential equity grant. A wide range of factors are considered in making compensation decisions, including but not limited to skill sets, market conditions, experience and training, licensure and certifications, and business and organizational needs.
Benefits and Employee Perks
- Competitive compensation and equity grant at a high-growth start up
- Comprehensive benefits package including medical, dental and vision insurance, and 401k
- Flexible hours and unlimited PTO
- Diverse and inclusive working environment
Verse is an equal opportunity employer. All applicants and employees are considered for hire, promotion, and compensation without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, marital or familial status.
Ready to apply?
Apply to Verse
Member of Technical Staff - ML Infrastructure Engineer
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About Black Forest Labs
We’re the team behind Latent Diffusion, Stable Diffusion, and FLUX—foundational technologies that changed how the world creates images and video. We’re creating the generative models that power how people make images and video—tools used by millions of creators, developers, and businesses worldwide. Our FLUX models are among the most advanced in the world, and we’re just getting started.
Headquartered in Freiburg, Germany with a growing presence in San Francisco, we’re scaling fast while staying true to what makes us different: research excellence, open science, and building technology that expands human creativity.
Why This Role
You'll design, deploy, and maintain the ML infrastructure backbone that makes frontier AI research possible. This isn't abstract systems work—every decision you make directly impacts whether a multi-week training run succeeds, whether inference stays fast enough for production, whether researchers can iterate quickly or wait hours for resources.
What You’ll Work On
You'll be the person who:
- Designs, deploys, and maintains cloud-based ML training clusters (Slurm) and inference clusters (Kubernetes) that researchers and products depend on
- Implements and manages network-based cloud file systems and blob/S3 storage solutions optimized for ML workloads at scale
- Develops and maintains Infrastructure as Code (IaC) for resource provisioning—because manual configuration doesn't scale and configuration drift breaks things
- Implements and optimizes CI/CD pipelines for ML workflows, making it easy for researchers to go from experiment to production
- Designs and implements custom autoscaling solutions for ML workloads where standard approaches fall short
- Ensures security best practices across the ML infrastructure stack without creating friction that slows down research
- Provides developer-friendly tools and practices that make ML operations efficient—because infrastructure that's hard to use doesn't get used
What We’re Looking For
You've built and managed ML infrastructure at scale and understand that supporting AI research is fundamentally different from traditional cloud infrastructure. You've been paged because a training run failed. You've debugged why storage became the bottleneck. You know the difference between infrastructure that works in demos and infrastructure that works when researchers depend on it for months-long experiments.
You likely have:
- Strong proficiency in cloud platforms (AWS, Azure, or GCP) with focus on ML/AI services—you know which services matter and which are marketing
- Extensive experience with Kubernetes and Slurm cluster management in production environments
- Expertise in Infrastructure as Code tools (Terraform, Ansible, etc.) and the discipline to actually use them
- Proven track record managing and optimizing network-based cloud file systems and object storage for ML workloads
- Experience with CI/CD tools and practices (CircleCI, GitHub Actions, ArgoCD, etc.) in ML contexts
- Strong understanding of security principles and best practices in cloud environments—without making security the enemy of velocity
- Experience with monitoring and observability tools (Prometheus, Grafana, Loki, etc.) that help you understand what's actually happening
- Familiarity with ML workflows and GPU infrastructure management—you understand what researchers need
- Demonstrated ability to handle complex migrations and breaking changes in production environments without losing data or breaking experiments
We'd be especially excited if you:
- Have experience building custom autoscaling solutions for ML workloads that standard tools can't handle
- Bring knowledge of cost optimization strategies for cloud-based ML infrastructure (because GPU hours add up)
- Are familiar with MLOps practices and tools
- Have experience with high-performance computing (HPC) environments
- Understand data versioning and experiment tracking for ML
- Know network optimization techniques for distributed ML training
- Have worked with multi-cloud or hybrid cloud architectures
- Are familiar with container security and vulnerability scanning tools
How We Work Together
We’re a distributed team with real offices that people actually use. Depending on your role, you’ll either join us in Freiburg or SF at least 2 days a week (or one full week every other week), or work remotely with a monthly in-person week to stay connected. We’ll cover reasonable travel costs to make this possible. We think in-person time matters, and we’ve structured things to make it accessible to all. We’ll discuss what this will look like for the role during our interview process.
Everything we do is grounded in four values:
- Obsessed. We are a frontier research lab. The science has to be right, the understanding deep, the product beautiful.
- Low Ego. The work speaks. The best idea wins, no matter who said it. Credit is shared. Nobody is above any task.
- Bold. We take the ambitious bet. We ship, we do not wait for conditions to be perfect.
- Kind. People over politics. We treat each other with genuine warmth. Agency without empathy creates chaos.
If this sounds like work you’d enjoy, we’d love to hear from you.
Base Annual Salary: $180,000–$300,000 USD
We're based in Europe and value depth over noise, collaboration over hero culture, and honest technical conversations over hype. Our models have been downloaded hundreds of millions of times, but we're still a ~50-person team learning what's possible at the edge of generative AI.
Ready to apply?
Apply to Black Forest Labs
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
The Data Science team at Asana is pivotal in fulfilling our mission by fostering a data-driven approach in shaping both our product and business strategies. In your role on the Marketing Data Science team, you will be the deepest technical expert responsible for using data and scientific techniques to design and build scalable, state-of-the-art solutions to enhance Asana’s marketing effectiveness. You will drive the technical roadmap for data science, collaborating with marketing leadership and the broader Asana data community to uncover new opportunities. You will provide technical leadership and hands-on mentorship, elevating the team's technical bar and influencing overall business strategy through best-in-class modeling and experimental design.
This role is based in our New York City office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements.
What you’ll achieve:
- Architect, design, and lead the technical execution for the Marketing Data Science roadmap, serving as the Solution Architect for all core projects including Media Mix Modeling (MMM), User Lifetime Value, Causal Inferences, Multi-touch Attribution, and Spend Optimization engines.
- Act as the primary technical subject matter expert for the Marketing Data Science team, setting the technical bar for modeling quality, code rigor, data pipeline architecture, and solution scalability.
- Collaborate with marketing leadership to pinpoint how data science can be further integrated into Asana's business approach.
- Provide hands-on technical mentorship and guidance to a team of data scientists at varying levels, helping them navigate complex modeling challenges, choose appropriate methodologies, and establish robust ML Ops.
- Develop and standardize MLOps tooling and processes that enable the team to deploy, monitor, and maintain multiple models in production efficiently and reliably.
- Research, prototype, and advocate for emerging capabilities and state-of-the-art models in the marketing data science space, demonstrating their potential benefits and leading their implementation.
- Take on a technical leadership role within the broader Asana Data Community, interacting with Data Engineering and Platform teams to influence the data and MLOps infrastructure required to support marketing data products.
About you:
- Bachelor Degree in Math, Statistics, Computer Science, Engineering a related quantitative field, or equivalent experience
- 6+ years of experience in a data science role, with 2+ years dedicated to technical leadership and mentorship of other data scientists, successfully driving the architecture and execution of large-scale production data science projects
- 4+ years of experience collaborating with Marketing functions on deep technical projects, with extensive experience designing, implementing, and deploying marketing models (e.g. MMM, LTV, MTA, Uplift)
- Expert-level knowledge in advanced statistical modeling, causal inference, experimental design and analysis, and machine learning techniques relevant to marketing effectiveness
- Proven track record developing, deploying, and maintaining scalable production ML solutions and data products
- Technical Stack: Expert proficiency in SQL and Python. Experience with MLOps tools (e.g., MLFlow), statistical languages (e.g., R), and distributed data processing systems (e.g., Spark, Redshift) is a plus
- Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making.
What we’ll offer:
Our comprehensive compensation package plays a big part in how we recognize you for the impact you have on our path to achieving our mission. We believe that compensation should be reflective of the value you create relative to the market value of your role. To ensure pay is fair and not impacted by biases, we're committed to looking at market value which is why we check ourselves and conduct a yearly pay equity audit.
For this role, the estimated base salary range is between $202,000 - $282,000. The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process. The listed range above is a guideline, and the base salary range for this role may be modified.
In addition to base salary, your compensation package may include additional components such as equity, sales incentive pay (for most sales roles), and benefits. If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role.
We strive to provide equitable and competitive benefits packages that support our employees worldwide and include:
- Mental health, wellness & fitness benefits
- Career coaching & support
- Inclusive family building benefits
- Long-term savings or retirement plans
- In-office culinary options to cater to your dietary preferences
These are just some of the benefits we offer, and benefits may vary based on role, country, and local regulations. If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role.
#LI-Hybrid #LI-AA1
About us
Asana is a leading platform for human + AI collaboration. Millions of teams around the world rely on Asana to achieve their most important goals, faster. Asana has been named to Fortune's Best Workplaces for 7+ years and recognized by Fast Company, Forbes, and Gartner for excellence in workplace culture and innovation. We offer an exceptional office-centric culture while adopting the best elements of hybrid models to ensure that every one of our global team members can work together effortlessly. With 13+ offices all over the world, we are always looking for individuals who care about building technology that drives positive change in the world and a culture where everyone feels that they belong.
Join Asana’s Talent Network to stay up to date on job opportunities and life at Asana.
Ready to apply?
Apply to Asana
The Data Science team at Asana is pivotal in fulfilling our mission by fostering a data-driven approach in shaping both our product and business strategies. In your role on the Marketing Data Science team, you will be the deepest technical expert responsible for using data and scientific techniques to design and build scalable, state-of-the-art solutions to enhance Asana’s marketing effectiveness. You will drive the technical roadmap for data science, collaborating with marketing leadership and the broader Asana data community to uncover new opportunities. You will provide technical leadership and hands-on mentorship, elevating the team's technical bar and influencing overall business strategy through best-in-class modeling and experimental design.
This role is based in our San Francisco office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements.
What you’ll achieve:
- Architect, design, and lead the technical execution for the Marketing Data Science roadmap, serving as the Solution Architect for all core projects including Media Mix Modeling (MMM), User Lifetime Value, Causal Inferences, Multi-touch Attribution, and Spend Optimization engines.
- Act as the primary technical subject matter expert for the Marketing Data Science team, setting the technical bar for modeling quality, code rigor, data pipeline architecture, and solution scalability.
- Collaborate with marketing leadership to pinpoint how data science can be further integrated into Asana's business approach.
- Provide hands-on technical mentorship and guidance to a team of data scientists at varying levels, helping them navigate complex modeling challenges, choose appropriate methodologies, and establish robust ML Ops.
- Develop and standardize MLOps tooling and processes that enable the team to deploy, monitor, and maintain multiple models in production efficiently and reliably.
- Research, prototype, and advocate for emerging capabilities and state-of-the-art models in the marketing data science space, demonstrating their potential benefits and leading their implementation.
- Take on a technical leadership role within the broader Asana Data Community, interacting with Data Engineering and Platform teams to influence the data and MLOps infrastructure required to support marketing data products.
About you:
- Bachelor Degree in Math, Statistics, Computer Science, Engineering a related quantitative field, or equivalent experience
- 6+ years of experience in a data science role, with 2+ years dedicated to technical leadership and mentorship of other data scientists, successfully driving the architecture and execution of large-scale production data science projects
- 4+ years of experience collaborating with Marketing functions on deep technical projects, with extensive experience designing, implementing, and deploying marketing models (e.g. MMM, LTV, MTA, Uplift)
- Expert-level knowledge in advanced statistical modeling, causal inference, experimental design and analysis, and machine learning techniques relevant to marketing effectiveness
- Proven track record developing, deploying, and maintaining scalable production ML solutions and data products
- Technical Stack: Expert proficiency in SQL and Python. Experience with MLOps tools (e.g., MLFlow), statistical languages (e.g., R), and distributed data processing systems (e.g., Spark, Redshift) is a plus
- Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making.
What we’ll offer:
Our comprehensive compensation package plays a big part in how we recognize you for the impact you have on our path to achieving our mission. We believe that compensation should be reflective of the value you create relative to the market value of your role. To ensure pay is fair and not impacted by biases, we're committed to looking at market value which is why we check ourselves and conduct a yearly pay equity audit.
For this role, the estimated base salary range is between $202,000 - $282,000. The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process. The listed range above is a guideline, and the base salary range for this role may be modified.
In addition to base salary, your compensation package may include additional components such as equity, sales incentive pay (for most sales roles), and benefits. If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role.
We strive to provide equitable and competitive benefits packages that support our employees worldwide and include:
- Mental health, wellness & fitness benefits
- Career coaching & support
- Inclusive family building benefits
- Long-term savings or retirement plans
- In-office culinary options to cater to your dietary preferences
These are just some of the benefits we offer, and benefits may vary based on role, country, and local regulations. If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role.
#LI-Hybrid #LI-AA1
About us
Asana is a leading platform for human + AI collaboration. Millions of teams around the world rely on Asana to achieve their most important goals, faster. Asana has been named to Fortune's Best Workplaces for 7+ years and recognized by Fast Company, Forbes, and Gartner for excellence in workplace culture and innovation. We offer an exceptional office-centric culture while adopting the best elements of hybrid models to ensure that every one of our global team members can work together effortlessly. With 13+ offices all over the world, we are always looking for individuals who care about building technology that drives positive change in the world and a culture where everyone feels that they belong.
Join Asana’s Talent Network to stay up to date on job opportunities and life at Asana.
Ready to apply?
Apply to Asana
AI Solutions Engineer, Post Sales Scale - W&B
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What You’ll Do
The Field Engineering team at Weights & Biases plays a vital role in ensuring customer success and adoption of our platform. As part of this team, we partner with Sales, Support, Product, and Engineering to lead technical success after the sales process. We work closely with some of the most advanced AI teams in the world, helping them build, optimize, and scale their ML and GenAI workflows across industries such as computer vision, robotics, natural language processing, and large language models (LLMs).
About the Role
We’re hiring a Post-Sales AI Solutions Engineer (AISE), Scale Customer Success to help customers successfully implement and scale AI/ML workflows and GenAI/agentic applications on Weights & Biases. You will design and deliver technical enablement and adoption programs that reach many customers at once, create reusable assets that improve self-serve success, and use product signals and feedback loops to continuously improve outcomes.
Key Responsibilities
- Run 1-to-many onboarding and enablement programs
Own and deliver scalable onboarding and adoption motions (webinars, cohort sessions, group training, and office hours) that help customers get to value quickly and consistently. - Build reusable technical assets that drive self-serve success
Create and maintain playbooks, reference architectures, templates, sample code/notebooks, and troubleshooting guides that standardize best practices and reduce repeated 1:1 work. - Operate the scaled motion using signals and feedback loops
Use product usage signals and customer patterns to segment and trigger the right interventions, track program impact (activation, time-to-first-value, feature adoption), and feed recurring insights back to Support, Product, and Field Engineering to continuously improve the scaled journey.
Who You Are
- 3–5 years of relevant experience in a similar role
- Strong programming proficiency in Python
- Experience with deep learning frameworks (TensorFlow/Keras, PyTorch Lightning) and tools (e.g., Streamlit, LangChain)
- Familiarity with cloud platforms (AWS, GCP, Azure)
- Excellent communication and presentation skills, both written and verbal
- Organized and outcomes-driven: you can run programs, measure impact, and iterate.
Preferred
- Experience with GenAI and LLMs
- Proficiency with HuggingFace, Fastai, scikit-learn, XGBoost, LightGBM, or Ray
- Experience with hyperparameter optimization solutions
- Background in data engineering, MLOps, or LLMOps, with tools such as Docker and Kubernetes
- Familiarity with data pipeline tools
Wondering if you’re a good fit?
We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren't a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk.
- You love collaborating with top AI teams to solve real-world ML and GenAI challenges
- You’re curious about how to optimize AI workflows at scale
- You’re an expert in Python and ML tooling, with a passion for enabling customer success
Why Us?
We work hard, have fun, and move fast! We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values:
- Be Curious at Your Core
- Act Like an Owner
- Empower Employees
- Deliver Best-in-Class Client Experiences
- Achieve More Together
We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and provides the opportunity to develop innovative solutions to complex problems. As we get set for takeoff, the growth opportunities within the organization are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us!
The base salary range for this role is $139,000 to $204,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).
What We Offer
The range we’ve posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location.
In addition to a competitive salary, we offer a variety of benefits to support your needs, including:
- Medical, dental, and vision insurance - 100% paid for by CoreWeave
- Company-paid Life Insurance
- Voluntary supplemental life insurance
- Short and long-term disability insurance
- Flexible Spending Account
- Health Savings Account
- Tuition Reimbursement
- Ability to Participate in Employee Stock Purchase Program (ESPP)
- Mental Wellness Benefits through Spring Health
- Family-Forming support provided by Carrot
- Paid Parental Leave
- Flexible, full-service childcare support with Kinside
- 401(k) with a generous employer match
- Flexible PTO
- Catered lunch each day in our office and data center locations
- A casual work environment
- A work culture focused on innovative disruption
Our Workplace
While we prioritize a hybrid work environment, remote work may be considered for candidates located more than 30 miles from an office, based on role requirements for specialized skill sets. New hires will be invited to attend onboarding at one of our hubs within their first month. Teams also gather quarterly to support collaboration.
California Consumer Privacy Act - California applicants only
CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information.
As part of this commitment and consistent with the Americans with Disabilities Act (ADA), CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: careers@coreweave.com.
Export Control Compliance
This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency. CoreWeave may, for legitimate business reasons, decline to pursue any export licensing process.
Ready to apply?
Apply to CoreWeave
Account Manager (W&B)
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What You’ll Do:
The Account Manager owns the commercial and relationship aspects of the post-sales journey across a portfolio of Digital Native and select Enterprise customers. You will drive renewals, identify and close upsell and cross-sell opportunities, and ensure customers achieve measurable adoption outcomes with Weights & Biases (W&B). You’ll partner closely with Field Engineering (FE)—who leads technical success—while you lead the commercial motions including renewal execution, usage-to-value alignment, growth pipeline creation, and multi-threaded stakeholder engagement.
About the role:
You will own renewals and lead commercial execution across your assigned accounts, including identifying and closing upsell and cross-sell opportunities. You will partner closely with Field Engineering (FE) while running the commercial motions: renewal execution, usage-to-value alignment, growth pipeline creation, and multi-threaded stakeholder engagement. You will maintain detailed account plans (account maps, whitespace, usage trends, risks, and growth opportunities) and maintain weekly forecasting accuracy and CRM hygiene across renewals and growth motions. This role requires comfort engaging highly technical personas (ML engineers, researchers, PhDs) and operating with autonomy in a rapidly evolving AI ecosystem; it is not a playbook-driven role.
- Own renewals, upsells, and cross-sells across your assigned accounts.
- Build and maintain detailed account plans including account maps, whitespace, usage trends, risks, and growth opportunities.
- Generate growth pipeline by identifying new use cases, teams, and product opportunities within existing accounts.
Who You Are:
- Based in the Bay Area (San Francisco, Peninsula, South Bay) strongly preferred; secondary options: New York City or Northern NJ.
- 6+ years in B2B/SaaS customer-facing roles commercializing technical products.
- 3+ years in a quota-carrying Account Management, Sales, or Renewals role owning post-sales outcomes.
- Strong, genuine interest in AI/ML and the evolving machine learning ecosystem.
- High technical and product curiosity; comfortable speaking with developers, ML engineers, and researchers.
- Proven ability to drive growth motions (upsells, cross-sells) and manage retention in technical accounts.
- Strong operational discipline: forecasting accuracy, CRM hygiene, renewal cadence management.
- Thrives in ambiguity; able to self-direct and operate independently without detailed playbooks.
Preferred:
- Experience working with ML, MLOps, DevOps, or data infrastructure teams.
- Familiarity with Git, Jupyter, Python, PyTorch, or cloud platforms (AWS, GCP, Azure).
- Experience designing or executing account activation or expansion strategies.
- Exposure to AI-native companies, model builders, or generative AI workflows.
Wondering if you’re a good fit?
We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren’t a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk.
- You love owning renewals and growth motions while building multi-threaded stakeholder relationships.
- You’re curious about AI/ML and enjoy learning quickly in a rapidly evolving ecosystem.
- You’re an expert in operating with strong discipline across account plans, forecasting, and CRM hygiene to drive commercial outcomes.
The base salary range for this role is $95,000 to $130,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).
What We Offer
The range we’ve posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location.
In addition to a competitive salary, we offer a variety of benefits to support your needs, including:
- Medical, dental, and vision insurance - 100% paid for by CoreWeave
- Company-paid Life Insurance
- Voluntary supplemental life insurance
- Short and long-term disability insurance
- Flexible Spending Account
- Health Savings Account
- Tuition Reimbursement
- Ability to Participate in Employee Stock Purchase Program (ESPP)
- Mental Wellness Benefits through Spring Health
- Family-Forming support provided by Carrot
- Paid Parental Leave
- Flexible, full-service childcare support with Kinside
- 401(k) with a generous employer match
- Flexible PTO
- Catered lunch each day in our office and data center locations
- A casual work environment
- A work culture focused on innovative disruption
Our Workplace
While we prioritize a hybrid work environment, remote work may be considered for candidates located more than 30 miles from an office, based on role requirements for specialized skill sets. New hires will be invited to attend onboarding at one of our hubs within their first month. Teams also gather quarterly to support collaboration.
California Consumer Privacy Act - California applicants only
CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information.
As part of this commitment and consistent with the Americans with Disabilities Act (ADA), CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: careers@coreweave.com.
Export Control Compliance
This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency. CoreWeave may, for legitimate business reasons, decline to pursue any export licensing process.
Ready to apply?
Apply to CoreWeave
AI Solutions Engineer, Pre-Sales- W&B
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CoreWeave, the AI Hyperscaler™, acquired Weights & Biases to create the most powerful end-to-end platform to develop, deploy, and iterate AI faster. Since 2017, CoreWeave has operated a growing footprint of data centers covering every region of the US and across Europe, and was ranked as one of the TIME100 most influential companies of 2024. By bringing together CoreWeave’s industry-leading cloud infrastructure with the best-in-class tools AI practitioners know and love from Weights & Biases, we’re setting a new standard for how AI is built, trained, and scaled.
The integration of our teams and technologies is accelerating our shared mission: to empower developers with the tools and infrastructure they need to push the boundaries of what AI can do. From experiment tracking and model optimization to high-performance training clusters, agent building, and inference at scale, we’re combining forces to serve the full AI lifecycle — all in one seamless platform.
Weights & Biases has long been trusted by over 1,500 organizations — including Nvidia, Canva, Cohere, Meta, Snowflake, Square, Toyota, and Amazon — to build better models, AI agents and applications. Now, as part of CoreWeave, that impact is amplified across a broader ecosystem of AI innovators, researchers, and enterprises.
As we unite under one vision, we’re looking for bold thinkers and agile builders who are excited to shape the future of AI alongside us. If you're passionate about solving complex problems at the intersection of software, hardware, and AI, there's never been a more exciting time to join our team.
About the Role:
As an AI Solutions Engineer you will sit at the intersection of cutting-edge AI infrastructure and the world’s most ambitious AI teams. You will help customers design, deploy, and scale modern ML and GenAI systems using Weights & Biases and CoreWeave’s AI cloud. This role combines hands-on technical depth with strategic customer engagement — ideal for AI practitioners who enjoy building real systems, solving complex problems, and shaping how AI is developed and operationalized at scale.
What You’ll Do:
- Own the technical wins by building proof of value (PoVs). You’ll be partnering with Account Executives to drive discovery, solution design, and successful technical evaluations.
- Lead deep technical conversations with ML engineers, researchers, and platform teams to understand their AI/GenAI workloads and architect scalable solutions across the CoreWeave and Weights & Biases ecosystem .
- Design and deliver compelling live demos, proof-of-value engagements, and rapid prototypes showcasing experiment tracking, distributed training, agentic workflows, fine-tuning, evaluation, and inference at scale.
- Architect modern ML and GenAI systems including distributed training, RAG pipelines, multi-agent systems, LLM fine-tuning workflows, and inference solutions.
- Translate business objectives into measurable technical outcomes such as model quality improvements, cost reductions, performance gains, and faster iteration cycles.
- Serve as a trusted technical advisor, influencing architectural decisions and best practices across MLOps, LLMOps, and platform engineering.
- Partner closely with Product and Engineering to relay customer feedback, shape roadmap priorities, and improve the end-to-end AI developer experience.
Who You Are:
- 2+ years of experience in Solutions Engineering, ML Engineering, AI Engineering, or a similar customer-facing technical role.
- Bachelors degree in Computer Science, Data Science, Electrical Engineering, Statistics, Mathematics, or related field. Master in similar area of study preferred.
- Strong proficiency in Python (bonus: TypeScript/JavaScript) and experience building production-grade ML or GenAI applications.
- Hands-on experience training, fine-tuning, evaluating, debugging, and deploying deep learning or LLM-based systems.
- Experience with modern GenAI architectures including retrieval-augmented generation (RAG), tool-using agents, evaluation frameworks, and guardrails.
- Comfortable designing cloud-native architectures across AWS, GCP, or Azure, with working knowledge of containers, networking fundamentals, and security best practices.
- Able to whiteboard distributed training or inference architectures and then implement working prototypes that demonstrate real customer value.
- Excellent communication and storytelling skills, with the ability to translate complex technical concepts into business impact.
- Thrives in fast-paced environments and can manage multiple customer engagements simultaneously.
Preferred:
- Experience building and evaluating agentic applications using frameworks such as LangChain, DSPy, LlamaIndex, CrewAI, OpenClaw, or similar ecosystems. Ability to quickly adapt to new frameworks is a huge plus.
- Familiarity with vector databases, embeddings workflows, and LLM evaluation frameworks (e.g., Ragas, TruLens, DeepEval).
- Hands-on experience with Hugging Face Transformers, PEFT/LoRA/QLoRA fine-tuning, TRL, Unsloth, or similar fine-tuning stacks. Big plus if experience using RL to improve agentic systems.
- Experience operating distributed workloads using Slurm, Ray, or Kubernetes.
- Experience with inference optimization and serving frameworks such as vLLM, TensorRT-LLM, Triton, or TGI.
- Experience in MLOps/LLMOps platform engineering or supporting enterprise AI deployments.
The base salary range for this role is $165,000 to $242,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).
What We Offer
The range we’ve posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location.
In addition to a competitive salary, we offer a variety of benefits to support your needs, including:
- Medical, dental, and vision insurance - 100% paid for by CoreWeave
- Company-paid Life Insurance
- Voluntary supplemental life insurance
- Short and long-term disability insurance
- Flexible Spending Account
- Health Savings Account
- Tuition Reimbursement
- Ability to Participate in Employee Stock Purchase Program (ESPP)
- Mental Wellness Benefits through Spring Health
- Family-Forming support provided by Carrot
- Paid Parental Leave
- Flexible, full-service childcare support with Kinside
- 401(k) with a generous employer match
- Flexible PTO
- Catered lunch each day in our office and data center locations
- A casual work environment
- A work culture focused on innovative disruption
Our Workplace
While we prioritize a hybrid work environment, remote work may be considered for candidates located more than 30 miles from an office, based on role requirements for specialized skill sets. New hires will be invited to attend onboarding at one of our hubs within their first month. Teams also gather quarterly to support collaboration.
California Consumer Privacy Act - California applicants only
CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information.
As part of this commitment and consistent with the Americans with Disabilities Act (ADA), CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: careers@coreweave.com.
Export Control Compliance
This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency. CoreWeave may, for legitimate business reasons, decline to pursue any export licensing process.
Ready to apply?
Apply to CoreWeave
Senior Account Manager- Weights & Biases
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What You’ll Do:
The Account Management team at Weights & Biases (W&B) by CoreWeave, drives retention and revenue growth across our existing customer base by ensuring AI/ML teams achieve meaningful outcomes with our platform. We partner closely with Field Engineering—who leads technical success—to connect product adoption to business value, reduce friction in ML workflows, and uncover whitespace across organizations. Our team builds deep, multi-threaded relationships with technical and operational stakeholders, maintains disciplined forecasting and account planning, and identifies opportunities to expand W&B usage across teams and business units. We ensure customers realize long-term value while contributing to sustained company growth.
About the Role:
As a Senior Account Manager, you will own the commercial strategy and outcomes for a portfolio of Enterprise and select Strategic customers. You will lead complex renewals, manage multi-threaded expansion and cross-sell motions, and scale W&B adoption across multiple teams and business units. You will run structured commercial workflows—including discovery, qualification, value and ROI articulation, pricing, negotiation, and forecasting—while maintaining detailed multi-year account plans that incorporate whitespace, risks, and growth sequencing. You will partner closely with Field Engineering to coordinate cross-functional deliverables, lead executive business reviews, and use adoption insights to influence expansion strategy. This role requires strong commercial judgment, technical curiosity, and the ability to operate autonomously in ambiguous, fast-moving environments.
Who You Are:
- 8+ years in B2B SaaS customer-facing roles commercializing technical products
- 5+ years in a quota-carrying Account Management, Sales, or Renewals role owning commercial outcomes
- Proven success managing Enterprise or Strategic customers with multi-threaded stakeholder engagement (practitioners → team leads → executives)
- Experience leading complex expansion, cross-sell, POV, and negotiation cycles
- Strong technical and product curiosity with familiarity in AI/ML, DevOps, or data infrastructure tooling
- Demonstrated ability to maintain detailed account plans including whitespace mapping, risk tracking, and multi-year growth planning
- Disciplined forecasting and CRM hygiene across renewal and expansion pipelines
- Able to self-direct in ambiguous environments and independently drive commercial outcomes
- Comfortable partnering with Field Engineering to connect technical adoption with business value and commercial strategy
Preferred:
- Experience collaborating with Field Engineering, Product, Engineering, or Support in technical SaaS
- Familiarity with Git, Python, Jupyter, PyTorch, Kubernetes, or cloud platforms (AWS, GCP, Azure)
- Experience supporting or selling to ML, MLOps, DevOps, or data infrastructure teams
- Background working with AI-native startups, foundation model builders, or Enterprise ML teams
Wondering if you’re a good fit?
We believe in investing in our people and value candidates who bring diverse experiences—even if you don’t meet every listed requirement. You may be a great fit if:
- You love building long-term customer partnerships and uncovering high-impact expansion opportunities
- You’re curious about how AI and ML teams build, scale, and productionize models—and you enjoy staying close to the latest advances in the field
- You’re an expert in navigating complex SaaS commercial cycles, managing multi-threaded accounts, and driving multi-team expansions
Why CoreWeave?
At CoreWeave, we work hard, have fun, and move fast! We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values:
- Be Curious at Your Core
- Act Like an Owner
- Empower Employees
- Deliver Best-in-Class Client Experiences
- Achieve More Together
We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and provides the opportunity to develop innovative solutions to complex problems. As we get set for takeoff, the growth opportunities within the organization are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us!
The base salary range for this role is $165,000 to $189,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).
#LIjobs
What We Offer
The range we’ve posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location.
In addition to a competitive salary, we offer a variety of benefits to support your needs, including:
- Medical, dental, and vision insurance - 100% paid for by CoreWeave
- Company-paid Life Insurance
- Voluntary supplemental life insurance
- Short and long-term disability insurance
- Flexible Spending Account
- Health Savings Account
- Tuition Reimbursement
- Ability to Participate in Employee Stock Purchase Program (ESPP)
- Mental Wellness Benefits through Spring Health
- Family-Forming support provided by Carrot
- Paid Parental Leave
- Flexible, full-service childcare support with Kinside
- 401(k) with a generous employer match
- Flexible PTO
- Catered lunch each day in our office and data center locations
- A casual work environment
- A work culture focused on innovative disruption
Our Workplace
While we prioritize a hybrid work environment, remote work may be considered for candidates located more than 30 miles from an office, based on role requirements for specialized skill sets. New hires will be invited to attend onboarding at one of our hubs within their first month. Teams also gather quarterly to support collaboration.
California Consumer Privacy Act - California applicants only
CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information.
As part of this commitment and consistent with the Americans with Disabilities Act (ADA), CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: careers@coreweave.com.
Export Control Compliance
This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency. CoreWeave may, for legitimate business reasons, decline to pursue any export licensing process.
Ready to apply?
Apply to CoreWeave
Solutions Architect
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What You’ll Do
Our Solutions Architecture team at Weights & Biases is a unique hybrid organization, combining the deep technical skills of Site Reliability Engineering with the consultative expertise of Solutions Architecture. We focus on ensuring customers can successfully deploy and operate W&B across cloud and on-prem environments while delivering a best-in-class experience that accelerates ML adoption at scale.
About the Role
As a Solutions Architect, you will be responsible for managing complex customer deployments across AWS, GCP, Azure, and on-prem environments. You’ll partner directly with customer engineering teams to provision and monitor services, debug and resolve infrastructure issues, and ensure performance and scalability using SRE best practices. This role blends hands-on technical problem-solving with customer-facing engagement, including technical discussions, demos, workshops, and enablement content creation. You’ll work closely with Sales Engineering, Field Engineering, Support, and Product to drive adoption and influence our product roadmap based on customer feedback.
Who You Are
- Proven track record of systematically diagnosing and resolving infrastructure issues
- Experience in a customer-facing technical role
- Expertise in Docker, Kubernetes, Helm charts, networking, and cloud-managed services (e.g., MySQL, Object Stores)
- Strong fundamentals in Infrastructure as Code (IaC), preferably Terraform
- Proficiency with at least one cloud platform (AWS, GCP, Azure); experience across multiple platforms is a plus
- Strong Linux/Unix command line experience
- Basic proficiency in Python and familiarity with ML workflows or tools
Preferred
- Deep proficiency in Kubernetes design patterns, including Operators
- Familiarity with data engineering and MLOps tooling
- Experience as an educator or facilitator for technical training sessions, workshops, or demos
- SaaS, web service, or distributed systems operations experience
Wondering if you’re a good fit?
We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren't a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk.
- You love diving into infrastructure problems and solving them systematically
- You’re curious about how to scale complex ML systems in production environments
- You’re an expert in building and running containerized, distributed systems
Why Us?
We work hard, have fun, and move fast! We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values:
- Be Curious at Your Core
- Act Like an Owner
- Empower Employees
- Deliver Best-in-Class Client Experiences
- Achieve More Together
We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and provides the opportunity to develop innovative solutions to complex problems. As we get set for takeoff, the growth opportunities within the organization are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us!
The base salary ranges for this role is $180,000 to $200,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).
What We Offer
The range we’ve posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location.
In addition to a competitive salary, we offer a variety of benefits to support your needs, including:
- Medical, dental, and vision insurance - 100% paid for by CoreWeave
- Company-paid Life Insurance
- Voluntary supplemental life insurance
- Short and long-term disability insurance
- Flexible Spending Account
- Health Savings Account
- Tuition Reimbursement
- Ability to Participate in Employee Stock Purchase Program (ESPP)
- Mental Wellness Benefits through Spring Health
- Family-Forming support provided by Carrot
- Paid Parental Leave
- Flexible, full-service childcare support with Kinside
- 401(k) with a generous employer match
- Flexible PTO
- Catered lunch each day in our office and data center locations
- A casual work environment
- A work culture focused on innovative disruption
Our Workplace
While we prioritize a hybrid work environment, remote work may be considered for candidates located more than 30 miles from an office, based on role requirements for specialized skill sets. New hires will be invited to attend onboarding at one of our hubs within their first month. Teams also gather quarterly to support collaboration.
California Consumer Privacy Act - California applicants only
CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information.
As part of this commitment and consistent with the Americans with Disabilities Act (ADA), CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: careers@coreweave.com.
Export Control Compliance
This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency. CoreWeave may, for legitimate business reasons, decline to pursue any export licensing process.
Ready to apply?
Apply to CoreWeave
Staff AI Security Engineer
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About the Role:
CoreWeave is seeking a Staff AI Security Engineer to define and operationalize security across our AI ecosystem. This role sits at the intersection of AI/ML, cloud infrastructure, and security engineering. You'll build secure-by-default foundations for AI development, agentic workflows, and enterprise AI adoption, balancing velocity with strong security guarantees. You will also partner closely with enterprise security and IT teams to manage AI-adjacent risks across the corporate environment, including shadow AI, data exfiltration through AI tooling, and SaaS security posture for AI-enabled platforms.
What You'll Do:
- Design and implement security controls across AI/ML infrastructure, including model artifact storage, data lineage and integrity, model signing and provenance, and ML pipeline security (MLOps/MLSecOps)
- Develop AI security policies, standards, and threat models covering model development, training pipelines, data ingestion, inference environments, and agentic systems
- Build security guardrails for agentic workflows: tool access and permissioning, input/output validation, execution boundaries, sandboxing, and auditability of agent actions
- Lead secure adoption of AI tools across engineering, security, operations, and enterprise functions. Evaluate AI vendors, copilots, and integrations. Define policies for data sharing, model usage boundaries, and sensitive data handling in prompts and outputs
- Partner with enterprise security and IT on AI-related risks across the corporate environment, including endpoint posture, corporate identity, and SaaS security for AI-enabled platforms
- Conduct threat modeling and adversarial testing of AI systems, covering prompt injection, data poisoning, model extraction, and backdoored models. Build and maintain a CoreWeave-specific AI threat taxonomy
- Drive cross-team technical decisions and influence architecture across platform engineering, security engineering, ML/AI teams, and product/DevEx to embed security into AI platforms and developer tooling
Who You Are:
Minimum Qualifications
- 10+ years of experience in security engineering (cloud, application, or infrastructure)
- Experience with AI/ML systems: LLMs, training pipelines, inference systems, or MLOps
- Strong, demonstrable experience building and securing large-scale distributed systems
- Strong coding skills in Go, Python, or similar
- Familiarity with Kubernetes, containerized environments, and cloud platforms (AWS, GCP, Azure)
- Understanding of AI-specific threats: prompt injection, data leakage, model misuse, supply chain risks in models and datasets
- Track record of driving cross-team technical initiatives and influencing architecture decisions at the org level
Preferred:
- Experience building or securing LLM-based systems, agent frameworks (LangChain, etc.), or AI-powered internal tools
- Background in adversarial ML or red teaming AI systems
- Experience with secure model deployment pipelines or confidential computing / secure enclaves
- Familiarity with identity and access control systems
- Experience in high-performance or GPU-centric environments
Why CoreWeave?
At CoreWeave, we work hard, have fun, and move fast! We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values:
- Be Curious at Your Core
- Act Like an Owner
- Empower Employees
- Deliver Best-in-Class Client Experiences
- Achieve More Together
We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and enables the development of innovative solutions to complex problems. As we get set for takeoff, the organization's growth opportunities are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us!
The base salary range for this role is $188,000 to $275,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).
What We Offer
The range we’ve posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location.
In addition to a competitive salary, we offer a variety of benefits to support your needs, including:
- Medical, dental, and vision insurance - 100% paid for by CoreWeave
- Company-paid Life Insurance
- Voluntary supplemental life insurance
- Short and long-term disability insurance
- Flexible Spending Account
- Health Savings Account
- Tuition Reimbursement
- Ability to Participate in Employee Stock Purchase Program (ESPP)
- Mental Wellness Benefits through Spring Health
- Family-Forming support provided by Carrot
- Paid Parental Leave
- Flexible, full-service childcare support with Kinside
- 401(k) with a generous employer match
- Flexible PTO
- Catered lunch each day in our office and data center locations
- A casual work environment
- A work culture focused on innovative disruption
Our Workplace
While we prioritize a hybrid work environment, remote work may be considered for candidates located more than 30 miles from an office, based on role requirements for specialized skill sets. New hires will be invited to attend onboarding at one of our hubs within their first month. Teams also gather quarterly to support collaboration.
California Consumer Privacy Act - California applicants only
CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information.
As part of this commitment and consistent with the Americans with Disabilities Act (ADA), CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: careers@coreweave.com.
Export Control Compliance
This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency. CoreWeave may, for legitimate business reasons, decline to pursue any export licensing process.
Ready to apply?
Apply to CoreWeave
At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.
With over half a billion rides and counting, Lyft is solving hard problems at scale, leveraging AI and Machine Learning to better serve our customers. The Artificial Intelligence, Machine Learning, and Operations Research Platforms team (AIMLOR) is seeking a Senior Machine Learning Engineer to focus on building AI Platform components enabling critical AI applications across Lyft. Expertise with GenAI and platform building is a core requirement for this role. In this role, you will contribute to our platform which supports real-time, online, and offline AI and ML model execution, development, and iteration. You will work with a team of highly motivated Machine Learning and Software Engineers on challenging problems, defining solutions to directly impact systems across the entire business.
If you are interested in building an AI Platform at scale, with applications across each facet of the company, we are searching for you.
If you are a creative and critical thinker with experience in AI and machine learning systems, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you.
Responsibilities:
- Contribute to the roadmap and architecture based on technology and business needs
- Write well-crafted, well-tested, readable, maintainable code
- Have a good grasp and ability to explain the various tradeoffs made in decisions
- Participate in code reviews to ensure code quality and distribute knowledge
- Build features from tech specification to positive execution
- Incorporate considerations for business context and failure modes in your work
- Proactively participate in resolving ongoing incidents
- Unblock, support, effectively communicate, and obtain buy-in within your team to achieve results
- Share your knowledge by giving brown bags and tech talks
Experience:
- BSc/MSc in Computer Engineering, Computer Science, Machine Learning related field or relevant work experience
- 5+ years of ML engineering experience working in any of these stacks: Python, GO, Java, etc.
- Experience with ML serving/training/deployment infrastructure; familiarity with cloud providers (e.g. AWS, Azure, Google Cloud); familiarity with GenAI ecosystem: LLMs, prompt engineering, MCP, RAG; hands-on experience with LLM fine-tuning techniques and frameworks (e.g. PEFT, LoRA); knowledge on deploying self-hosted LLMs (e.g. Llama, Mistral) for specialized tasks
- Experience with GenAI/LLM infrastructure, agent frameworks (e.g. LangChain, LangGraph); MLOps tooling (MLflow, Airflow)
- Preferred: Experience with AI assisted coding such as Cursor or Claude Code
Benefits:
- Great medical, dental, and vision insurance options with additional programs available when enrolled
- Mental health benefits
- Family building benefits
- Child care and pet benefits
- 401(k) plan with company match to help save for your future
- In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
- 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
- Subsidized commuter benefits
- Monthly Lyft credits and complimentary Lyft Pink membership
Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.
Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid
The expected base pay range for this position in the San Francisco area is $162,800 - $203,500, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.
Ready to apply?
Apply to Lyft
At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.
With over half a billion rides and counting, Lyft is solving hard problems at scale, leveraging AI and Machine Learning to better serve our customers. The Artificial Intelligence, Machine Learning, and Operations Research Platforms team (AIMLOR) is seeking a Senior Machine Learning Engineer to focus on building AI Platform components enabling critical AI applications across Lyft. Expertise with GenAI and platform building is a core requirement for this role. In this role, you will contribute to our platform which supports real-time, online, and offline AI and ML model execution, development, and iteration. You will work with a team of highly motivated Machine Learning and Software Engineers on challenging problems, defining solutions to directly impact systems across the entire business.
If you are interested in building an AI Platform at scale, with applications across each facet of the company, we are searching for you.
If you are a creative and critical thinker with experience in AI and machine learning systems, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you.
Responsibilities:
- Contribute to the roadmap and architecture based on technology and business needs
- Write well-crafted, well-tested, readable, maintainable code
- Have a good grasp and ability to explain the various tradeoffs made in decisions
- Participate in code reviews to ensure code quality and distribute knowledge
- Build features from tech specification to positive execution
- Incorporate considerations for business context and failure modes in your work
- Proactively participate in resolving ongoing incidents
- Unblock, support, effectively communicate, and obtain buy-in within your team to achieve results
- Share your knowledge by giving brown bags and tech talks
Experience:
- BSc/MSc in Computer Engineering, Computer Science, Machine Learning related field or relevant work experience
- 5+ years of ML engineering experience working in any of these stacks: Python, GO, Java, etc.
- Experience with ML serving/training/deployment infrastructure; familiarity with cloud providers (e.g. AWS, Azure, Google Cloud); familiarity with GenAI ecosystem: LLMs, prompt engineering, MCP, RAG; hands-on experience with LLM fine-tuning techniques and frameworks (e.g. PEFT, LoRA); knowledge on deploying self-hosted LLMs (e.g. Llama, Mistral) for specialized tasks
- Experience with GenAI/LLM infrastructure, agent frameworks (e.g. LangChain, LangGraph); MLOps tooling (MLflow, Airflow)
- Preferred: Experience with AI assisted coding such as Cursor or Claude Code
Benefits:
- Great medical, dental, and vision insurance options with additional programs available when enrolled
- Mental health benefits
- Family building benefits
- Child care and pet benefits
- 401(k) plan with company match to help save for your future
- In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
- 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
- Subsidized commuter benefits
- Monthly Lyft credits and complimentary Lyft Pink membership
Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.
Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid
The expected base pay range for this position in the Seattle area is $149,780 - $187,220, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.
Ready to apply?
Apply to Lyft
Manager, Customer Success Engineering
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Dive in and do the best work of your career at DigitalOcean. Journey alongside a strong community of top talent who are relentless in their drive to build the simplest scalable cloud. If you have a growth mindset, naturally like to think big and bold, and are energized by the fast-paced environment of a true industry disruptor, you’ll find your place here. We value winning together—while learning, having fun, and making a profound difference for the dreamers and builders in the world.
We are looking for a Manager, Customer Success Engineering (AI & Cloud Support) who is passionate about delivering exceptional support experiences and building high-performing teams.
As a Manager, CSE (AI & Cloud Support) at DigitalOcean, you will operate as a Support Manager leading a team of Customer Success Engineers (CSEs) supporting strategic customers across cloud infrastructure and emerging AI/ML workloads. Reporting to the Senior Manager of Customer Success Engineering, you will own day-to-day support operations, team performance, and customer experience outcomes.
This role is focused on driving operational excellence while building strong technical depth within the team across AI, GPUs, Kubernetes, Databases and core cloud offerings. You will play a key role in ensuring consistent support coverage, developing SMEs, and partnering cross-functionally with Product and Engineering to improve both customer experience and product quality.
The ideal candidate brings a deep understanding of cloud and AI/ML ecosystems, including machine learning operations (MLOps), and enterprise support, combined with a passion for innovation and automation, and a proven ability to lead teams in delivering “white-glove” experiences for strategic customers.
What You’ll Do:
Team Leadership & Development
- Lead, hire, train, mentor and develop a high-performing team of Customer Success Engineers (CSEs), driving accountability, performance, and career growth
- Establish performance metrics (KPIs/SLAs) and conduct regular 1:1s, performance reviews, and career development planning.
- Own end-to-end support operations, including queue management, escalations, and shift planning to ensure consistent 24x7 coverage.
- Drive improvements in key support metrics such as CSAT, response times, resolution times, and overall support quality.
- Build and strengthen technical expertise within the team across core areas such as Kubernetes (DOKS), Databases, Compute, and AI/ML workloads.
Strategic Customer Support
- Act as the ultimate point of technical escalation for our largest, most strategic enterprise customers across Cloud and AI/ML workloads, stepping in to manage critical incidents and high-severity (Sev1/Sev2) issues.
- Design and implement customized support plans, SLAs, and escalation pathways tailored to the needs of strategic accounts.
- Partner closely with Technical Account Managers (TAMs), Growth Account Managers (GAM) to conduct Executive Business Reviews (EBRs) and ensure customers are maximizing the value of our Cloud and AI/ML products.
- Proactively identify risks and opportunities within strategic accounts to improve customer experience, adoption, and retention.
Technical & Cross-Functional Operations
- Serve as the Voice of the Customer (VoC) to Product and Engineering teams, synthesizing support data to advocate for bug fixes, feature requests, and UX improvements.
- Own and continuously improve escalation protocols between AI/ML Support and CloudOps, Infrastructure Engineering, and Product — including Jira escalation routing, Sev1 bridge management, and post-incident documentation.
- Own the development and maintenance of SOPs, escalation runbooks, HVC support playbooks, and knowledge base content — treating documentation infrastructure as a core operational lever for team scalability.
- Contribute to the vision for AI and automation within support—building intelligent tooling and driving the team toward an automation-first model to improve efficiency, scalability, and customer experience.
- Foster a culture of continuous learning, ensuring the team stays ahead of evolving cloud technologies, AI/ML frameworks, and industry trends.
Key Metrics:
- Customer Satisfaction (CSAT) for strategic accounts
- Time to Response and Resolution (TTR) for strategic customers
- Tier 1 resolution rate vs. escalation rate
- Time-to-escalation and engineering handoff SLA adherence
- SLA adherence and escalation response times
- Support productivity and quality (QA scores)
- Post-incident documentation completion rate
What You’ll Add to DigitalOcean:
- Experience: 5+ years of experience in Technical Support, Customer Success, or Technical Account Management within B2B SaaS, Cloud, or AI/ML environments ideally including experience supporting AI-native, high-growth companies with 24x7 production dependencies on GPU infrastructure.
- Leadership: 2+ years of people management experience leading technical, customer-facing teams, preferably in a high-growth, post-acquisition, or rapidly scaling environment.
- Technical Domain Expertise: Solid understanding of AI/ML concepts, including Generative AI, Large Language Models (LLMs), natural language processing (NLP), and MLOps. Deep familiarity with GPU infrastructure (NVIDIA H100/H200, bare metal GPU provisioning) and AI inference workloads is strongly preferred.
- Coding/Integration: Proficiency in reading and debugging code (Python preferred) and troubleshooting RESTful APIs and cloud architecture.
- Communication: Excellent verbal and written communication skills, with the ability to translate complex technical or AI concepts for diverse audiences OR to both highly technical engineers and non-technical business executives.
- Problem-Solving: Proven ability to remain calm under pressure and de-escalate high-stakes situations with enterprise clients.
Preferred Qualifications:
- Hands-on experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and AI toolchains (e.g., LangChain, Hugging Face).
- Experience with major cloud platforms (AWS, Google Cloud, Azure) and their native AI/ML services.
- Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related technical field.
- ITIL or equivalent service management certification
Compensation Range:
- $125,000 - $153,000
*This is a remote role
JR: 2026-7692
#LI-Remote
Why You’ll Like Working for DigitalOcean
- We innovate with purpose. You’ll be a part of a cutting-edge technology company with an upward trajectory, who are proud to simplify cloud and AI so builders can spend more time creating software that changes the world. As a member of the team, you will be a Shark who thinks big, bold, and scrappy, like an owner with a bias for action and a powerful sense of responsibility for customers, products, employees, and decisions.
- We prioritize career development. At DO, you’ll do the best work of your career. You will work with some of the smartest and most interesting people in the industry. We are a high-performance organization that will always challenge you to think big. Our organizational development team will provide you with resources to ensure you keep growing. We provide employees with reimbursement for relevant conferences, training, and education. All employees have access to LinkedIn Learning's 10,000+ courses to support their continued growth and development.
- We care about your well-being. Regardless of your location, we will provide you with a competitive array of benefits to support you from our Employee Assistance Program to Local Employee Meetups to flexible time off policy, to name a few. While the philosophy around our benefits is the same worldwide, specific benefits may vary based on local regulations and preferences.
- We reward our employees. The salary range for this position is based on market data, relevant years of experience, and skills. You may qualify for a bonus in addition to base salary; bonus amounts are determined based on company and individual performance. We also provide equity compensation to eligible employees, including equity grants upon hire and the option to participate in our Employee Stock Purchase Program.
- DigitalOcean is an equal-opportunity employer. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.
Application Limit: You may apply to a maximum of 3 positions within any 180-day period. This policy promotes better role-candidate matching and encourages thoughtful applications where your qualifications align most strongly.
Ready to apply?
Apply to DigitalOcean
Strategic Technical Account Manager, AI/ML
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Dive in and do the best work of your career at DigitalOcean. Journey alongside a strong community of top talent who are relentless in their drive to build the simplest scalable cloud. If you have a growth mindset, naturally like to think big and bold, and are energized by the fast-paced environment of a true industry disruptor, you’ll find your place here. We value winning together—while learning, having fun, and making a profound difference for the dreamers and builders in the world.
We are looking for a Strategic Technical Account Manager who is passionate about making an impact, builds genuine relationships with senior stakeholders, and understands how to integrate infrastructure choices into business strategy.
As a Strategic Technical Account Manager (TAM) at DigitalOcean, you will join a dynamic team dedicated to revolutionizing cloud computing and AI.
What You’ll Do:
Strategic Relationship Management
- Own the technical relationship with DigitalOcean’s highest-value customers, including Fortune 500 companies and global technology leaders.
- Serve as the trusted technical advisor and executive-facing point of contact, building deep, lasting relationships with VP- and SVP-level stakeholders.
- Drive regular technical and strategic alignment sessions (QBRs, EBRs), proactively shaping the customer’s roadmap to maximize the value of DigitalOcean infrastructure.
- Operate as a thought partner, challenging customers to modernize, optimize, and scale AI/ML and GPU workloads using cutting-edge cloud architecture patterns.
Executive Presence & Influence
- Engage with C-level and VP-level contacts with confidence, clarity, and authority.
- Deliver high-impact, boardroom-ready presentations on architecture decisions, cost-performance tradeoffs, and innovation opportunities.
- Navigate complex org structures, ensuring DigitalOcean maintains executive alignment and account control at every level.
Technical Consultation & Innovation Support
- Provide expert guidance on designing and scaling AI/ML, containerized, and GPU-intensive workloads on DigitalOcean.
- Assist customers with architectural planning, workload migration, performance tuning, and incident response.
- Collaborate directly with engineering and product teams to address customer roadblocks and influence the product roadmap based on enterprise needs.
Growth, Retention & Advocacy
- Own technical success across a portfolio of DigitalOcean’s largest and most strategic accounts.
- Identify opportunities for workload expansion, cost optimization, and operational efficiency.
- Act as the voice of the customer, providing structured feedback to influence DigitalOcean's offerings and go-to-market strategies.
Lead cross-functional account planning with Account Management, Product, and Engineering.
What You’ll Add to DigitalOcean:
Enterprise Customer Experience
- 7+ years supporting enterprise or strategic accounts in a customer-facing technical role (TAM, Solutions Architect, or equivalent).
- Experience working with large-scale organizations like AMD, Intel, or similar, including managing executive-level relationships and navigating matrixed stakeholders.
- Deep understanding of cloud architecture for AI/ML, including GPU orchestration, inference/training pipelines, and model deployment.
Technical Depth
- Proficient in at least one major cloud platform (AWS, GCP, Azure) and familiar with DigitalOcean or other developer-focused platforms.
- Strong hands-on skills with Linux systems, networking, containers (Docker/Kubernetes), and automation (Terraform, Ansible).
Programming/scripting in Python, Go, or similar—especially relevant to AI/ML and MLOps use cases. - Understanding of AI/ML infrastructure stacks: PyTorch, TensorFlow, ONNX, Hugging Face, NVIDIA Triton, etc.
- Understanding of AI/ML infrastructure, including frameworks like PyTorch, TensorFlow, and ONNX, with hands-on experience optimizing GPU workloads on both NVIDIA (CUDA, TensorRT) and AMD (ROCm, MIOpen) platforms.
- Comfort with modern DevOps and data stack tools (CI/CD, GitOps, observability, pipelines).
Executive Presence & Communication
- Proven ability to engage with and influence executive decision-makers.
- Exceptional communication skills, including the ability to translate complex technical topics into strategic business impact.
- Comfortable presenting to large audiences, running technical workshops, and defending architectural decisions.
Bonus Points
- Cloud certifications (AWS SA Pro, GCP PCA, Azure Architect) or NVIDIA certifications.
- Experience with high-performance computing, edge AI, or hybrid/multicloud strategies.
- Background in startup or high-growth environments where agility and influence matter.
- Familiarity with DigitalOcean’s developer ecosystem, API, and service portfolio.
Compensation Range:
- $174,240 - $217,800
*This is a remote role
#LI-Remote
Why You’ll Like Working for DigitalOcean
- We innovate with purpose. You’ll be a part of a cutting-edge technology company with an upward trajectory, who are proud to simplify cloud and AI so builders can spend more time creating software that changes the world. As a member of the team, you will be a Shark who thinks big, bold, and scrappy, like an owner with a bias for action and a powerful sense of responsibility for customers, products, employees, and decisions.
- We prioritize career development. At DO, you’ll do the best work of your career. You will work with some of the smartest and most interesting people in the industry. We are a high-performance organization that will always challenge you to think big. Our organizational development team will provide you with resources to ensure you keep growing. We provide employees with reimbursement for relevant conferences, training, and education. All employees have access to LinkedIn Learning's 10,000+ courses to support their continued growth and development.
- We care about your well-being. Regardless of your location, we will provide you with a competitive array of benefits to support you from our Employee Assistance Program to Local Employee Meetups to flexible time off policy, to name a few. While the philosophy around our benefits is the same worldwide, specific benefits may vary based on local regulations and preferences.
- We reward our employees. The salary range for this position is based on market data, relevant years of experience, and skills. You may qualify for a bonus in addition to base salary; bonus amounts are determined based on company and individual performance. We also provide equity compensation to eligible employees, including equity grants upon hire and the option to participate in our Employee Stock Purchase Program.
- DigitalOcean is an equal-opportunity employer. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.
Application Limit: You may apply to a maximum of 3 positions within any 180-day period. This policy promotes better role-candidate matching and encourages thoughtful applications where your qualifications align most strongly.
Ready to apply?
Apply to DigitalOcean
Senior Machine Learning Software Engineer (MLOps)
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Who We Are:
Calico (Calico Life Sciences LLC) is an Alphabet-founded research and development company whose mission is to harness advanced technologies and model systems to increase our understanding of the biology that controls human aging. Calico will use that knowledge to devise interventions that enable people to lead longer and healthier lives. Calico’s highly innovative technology labs, its commitment to curiosity-driven discovery science and, with academic and industry partners, its vibrant drug-development pipeline, together create an inspiring and exciting place to catalyze and enable medical breakthroughs.
Position Description:
Calico seeks a Senior Machine Learning Software Engineer (MLOps) to own the scaling, reliability, and deployment of our machine learning workloads. You will build the computational backbone to accelerate, scale, and productionize our ML research, serving as the critical bridge between frontier research and production-grade engineering.
If you are passionate about standardizing ML infrastructure, conquering complex distributed systems challenges, and being the core glue that wires up modern toolchains, this is the role for you.
Please note: No biology or life sciences background is required for this role.
Key Responsibilities:
You will work with a team of researchers and engineers on Calico’s key strategic cross-functional drug discovery and development initiatives through the following responsibilities:
- Architect the Computational Engine: Design, build, and deploy highly scalable distributed training environments and evaluate and establish the company-wide blueprint for orchestration systems and infrastructure for therapeutic discovery and development
- Build the Serving Infrastructure: Architect the high-throughput inference and serving pipelines necessary for our models to propose and evaluate synthesis recommendations
- Define the MLOps Standard: Architect and implement rigorous, automated systems for ML experiment tracking, model versioning, checkpointing, and artifact registries, ensuring our path to drug discovery is fully reproducible and data-driven
- Mentorship & Leadership: Serve as a subject matter expert and technical mentor, including partnering with our researchers and academic partners to integrate their research into our production pipelines
Position Requirements:
- A strong intellectual curiosity for life sciences
- 5+ years of relevant work experience in industry or academia
- Strong software engineering skills with deep expertise in Python and JAX or PyTorch
- Hands-on experience with MLOps practices (e.g., model registries, monitoring, CI/CD for ML pipelines) and modern open-source tools (e.g., Ray, Kubernetes, MLflow, Airflow, Flyte)
- Must be willing to work onsite at least four days a week
Nice to Have:
- Hands-on experience troubleshooting distributed training bottlenecks
- Prior experience productionizing ML models for biological or molecular data
- Contributions to open-source projects or academic publications in ML
The estimated base salary range for this role is $209,000 - $233,000. Actual pay will be based on a number of factors including experience and qualifications. This position is also eligible for two annual cash bonuses.
Ready to apply?
Apply to Calico
Senior Manager Data Scientist (Portfolio Management and Loss Mitigation)
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Employee Applicant Privacy Notice
Who we are:
Shape a brighter financial future with us.
Together with our members, we’re changing the way people think about and interact with personal finance.
We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world.
Senior Manager, Data Science
Portfolio Management and Loss Mitigation
The Role:
SoFi is seeking an inspirational and deeply experienced Senior Manager to lead the Portfolio Management and Loss Mitigation function in our Risk Data Science team. Reporting to the Head of Risk Data Science, this role will lead the development, deployment, and governance of portfolio management and loss mitigation models for all credit products.
The ideal candidate is a hands-on leader who can transition the team from traditional modeling to next-generation machine learning platforms, leveraging emerging data sources (e.g., cash flow, alternative bureaus) to significantly improve portfolio performance, reduce losses, and ensure rigorous adherence to Model Risk Management (MRM) standards. This role requires exceptional organizational leadership, an ability to influence stakeholders, and proven success in delivering complex models into a regulated production environment.
What You'll Do:
- Portfolio Management and Loss Mitigation Excellence: Directly oversee the development and deployment of Next Generation models designed to manage and mitigate portfolio losses while maintaining loss guardrails.
- Drive Next-Generation Capabilities: Incorporate industry trends and advanced techniques (NLP, Graph Mining, LLMs, Deep Learning) to solve complex, high-impact risk problems where established principles may not fully apply.
- Alternative Data Strategy: Spearhead the evaluation and integration of alternative data sources (Macro-Economic variables, tri-bureau, LexisNexis, cash flow data) to enhance predictive power across all credit products.
- Lead the current team of high-performing Staff and Senior Data Scientists. Recruit, mentor, and foster talent through deliberate interactions, succession planning, and creating a high-accountability, low-ego culture.
- Model Risk Management (MRM): Act as the primary owner for all models in the portfolio, ensuring robust documentation, monitoring, and successfully navigating the 2nd Line of Defense (2LOD) review and approval process (SR 11-7 familiarity is mandatory).
- Stakeholder Alignment: Interact and negotiate with senior management and external stakeholders to reconcile competing views and drive critical, high-impact business decisions.
- Automation and Efficiency: Lead efforts to automate model monitoring and governance processes to create scalable and auditable infrastructure.
What You'll Need:
- Experience: 8+ years of progressive experience in credit risk, modeling, and data science within a regulated financial institution (FinTech, Bank, or similar), with at least 3 years in a people management role, managing technical staff.
- Education: Master’s or Ph.D. degree in a quantitative field (Statistics, Computer Science, Engineering, Operations Research, etc.).
- Technical Acumen: Deep expertise in advanced statistical and machine learning modeling techniques (e.g., Gradient Boosting, Deep Learning, Causal Inference).
- Regulatory Knowledge: Detailed working knowledge of model risk management standards (e.g., SR 11-7) and the ability to operate within a highly regulated environment.
- Tools & Platforms: Expert-level proficiency in Python (PySpark, scikit-learn, TensorFlow/PyTorch) and SQL/data warehouse technologies (e.g., Snowflake, Hive). Familiarity with modern MLOps platforms and cloud computing (AWS).
- 3+ years of progressive people management experience is required, including the ability to recruit, mentor, and foster talent within a team of high-performing Staff and Senior Data Scientists.
- Communication: Ability to distill highly complex analytical concepts into clear, concise, and compelling narratives for non-technical leadership.
SoFi provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion (including religious dress and grooming practices), sex (including pregnancy, childbirth and related medical conditions, breastfeeding, and conditions related to breastfeeding), gender, gender identity, gender expression, national origin, ancestry, age (40 or over), physical or medical disability, medical condition, marital status, registered domestic partner status, sexual orientation, genetic information, military and/or veteran status, or any other basis prohibited by applicable state or federal law.
The Company hires the best qualified candidate for the job, without regard to protected characteristics.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
New York applicants: Notice of Employee Rights
SoFi is committed to an inclusive culture. As part of this commitment, SoFi offers reasonable accommodations to candidates with physical or mental disabilities. If you need accommodations to participate in the job application or interview process, please let your recruiter know or email accommodations@sofi.com.
Due to insurance coverage issues, we are unable to accommodate remote work from Hawaii or Alaska at this time.
Ready to apply?
Apply to SoFi
About Workato
Workato delivers enterprise infrastructure for the agentic era, redefining iPaaS and helping enterprises unify data, applications, processes, and AI into a single, governed platform. A leader in Enterprise MCP and trusted by 50% of the Fortune 500, Workato’s cloud-native architecture connects every application, data source, and process to power real-time orchestration at scale. With enterprise-grade security and continuous innovation at its core, Workato provides the trusted foundation for organizations to automate with confidence and operationalize AI across the business. To learn more, visit www.workato.com
Why join us?
Ultimately, Workato believes in fostering a flexible, trust-oriented culture that empowers everyone to take full ownership of their roles. We are driven by innovation and looking for team players who want to actively build our company.
But, we also believe in balancing productivity with self-care. That’s why we offer all of our employees a vibrant and dynamic work environment along with a multitude of benefits they can enjoy inside and outside of their work lives.
If this sounds right up your alley, please submit an application. We look forward to getting to know you!
Also, feel free to check out why:
-
Business Insider named us an “enterprise startup to bet your career on”
-
Forbes’ Cloud 100 recognized us as one of the top 100 private cloud companies in the world
-
Deloitte Tech Fast 500 ranked us as the 17th fastest growing tech company in the Bay Area, and 96th in North America
-
Quartz ranked us the #1 best company for remote workers
Responsibilities
We are seeking a product-minded Staff Software Engineer to join our San Francisco team focused on building the next generation of developer products. This role is at the forefront of innovation, specifically creating tools and platforms for developers who are building LLM and Agentic applications. You will be instrumental in shaping the future of how developers interact with and build on top of Workato's ecosystem in the age of AI. You will collaborate closely with product, engineering, and developer relations teams to deliver robust, scalable, and intuitive services. This role requires a high technical bar, plus an emphasis on developer ergonomics, so we can deliver a delightful developer experience.
-
Design, build, and maintain robust, scalable, and high-quality developer-facing products and APIs for LLM and Agentic application development.
-
Collaborate closely with product managers, designers, developer relations and other engineers to translate developer needs and product requirements into elegant technical solutions.
-
Write clean, maintainable, and well-tested code, and contribute to a high standard of engineering excellence within the team.
-
Implement and improve validation, monitoring, and observability for ML services within the sandbox environment.
-
Drive the full development lifecycle: from ideation and architecture to deployment and continuous improvement.
-
Continuously evaluate and optimize existing implementations for performance, scalability, and developer usability.
-
Identify and resolve bottlenecks, bugs, and technical challenges in a fast-paced, iterative environment.
-
Conduct code reviews and mentor team members to uphold high engineering standards.
-
Stay at the cutting edge of AI, LLMs, and developer tooling, bringing new ideas and technologies to the team.
-
This role is on-site in our San Francisco Office.
Requirements
Qualifications / Experience / Technical Skills
-
Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or equivalent industry experience.
-
8+ years of experience of professional software development experience, with a proven track record of shipping high-quality products.
-
You are a product-minded engineer who thinks deeply about the end-user. You have strong opinions about what makes a great developer experience.
-
You have experience building developer-facing products, APIs, SDKs, or CLIs.
-
You are proficient in one or more modern programming languages such as Go, Python, Ruby, or JavaScript and hands-on experience with LLM models.
-
Proven track record of deploying and maintaining ML services in production environments is a strong plus.
-
Solid understanding of API design, developer tooling, software architecture, data structures, and algorithms.
-
LLMops/MLops experience is a strong plus, especially in developer-facing products.
-
Experience building or supporting developer platforms, APIs, or sandbox environments is highly desirable.
Soft Skills / Personal Characteristics
-
Excellent written and verbal communication skills in English.
-
Collaborative team player with a passion for empowering developers and improving developer experience.
-
Adaptable, proactive, and creative—comfortable working in a dynamic, startup-like environment.
-
Strong problem-solving skills and a continuous improvement mindset.
Join us in San Francisco and help shape the future of developer innovation with AI-powered sandbox experiences!
(REQ ID: 2710)
Ready to apply?
Apply to Workato
About Workato
Workato delivers enterprise infrastructure for the agentic era, redefining iPaaS and helping enterprises unify data, applications, processes, and AI into a single, governed platform. A leader in Enterprise MCP and trusted by 50% of the Fortune 500, Workato’s cloud-native architecture connects every application, data source, and process to power real-time orchestration at scale. With enterprise-grade security and continuous innovation at its core, Workato provides the trusted foundation for organizations to automate with confidence and operationalize AI across the business. To learn more, visit www.workato.com
Why join us?
Ultimately, Workato believes in fostering a flexible, trust-oriented culture that empowers everyone to take full ownership of their roles. We are driven by innovation and looking for team players who want to actively build our company.
But, we also believe in balancing productivity with self-care. That’s why we offer all of our employees a vibrant and dynamic work environment along with a multitude of benefits they can enjoy inside and outside of their work lives.
If this sounds right up your alley, please submit an application. We look forward to getting to know you!
Also, feel free to check out why:
-
Business Insider named us an “enterprise startup to bet your career on”
-
Forbes’ Cloud 100 recognized us as one of the top 100 private cloud companies in the world
-
Deloitte Tech Fast 500 ranked us as the 17th fastest growing tech company in the Bay Area, and 96th in North America
-
Quartz ranked us the #1 best company for remote workers
Responsibilities
We are seeking a product-minded Senior Software Engineer to join our San Francisco team focused on building the next generation of developer products. This role is at the forefront of innovation, specifically creating tools and platforms for developers who are building LLM and Agentic applications. You will be instrumental in shaping the future of how developers interact with and build on top of Workato's ecosystem in the age of AI. You will collaborate closely with product, engineering, and developer relations teams to deliver robust, scalable, and intuitive services. This role requires a high technical bar, plus an emphasis on developer ergonomics, so we can deliver a delightful developer experience.
In this role, you will also be responsible to:
-
Design, build, and maintain robust, scalable, and high-quality developer-facing products and APIs for LLM and Agentic application development.
-
Collaborate closely with product managers, designers, developer relations and other engineers to translate developer needs and product requirements into elegant technical solutions.
-
Write clean, maintainable, and well-tested code, and contribute to a high standard of engineering excellence within the team.
-
Implement and improve validation, monitoring, and observability for ML services within the sandbox environment.
-
Drive the full development lifecycle: from ideation and architecture to deployment and continuous improvement.
-
Continuously evaluate and optimize existing implementations for performance, scalability, and developer usability.
-
Identify and resolve bottlenecks, bugs, and technical challenges in a fast-paced, iterative environment.
-
Conduct code reviews and mentor team members to uphold high engineering standards.
-
Stay at the cutting edge of AI, LLMs, and developer tooling, bringing new ideas and technologies to the team.
Requirements
Qualifications / Experience / Technical Skills
-
Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or equivalent industry experience.
-
5+ years of experience of professional software development experience, with a proven track record of shipping high-quality products.
-
You are a product-minded engineer who thinks deeply about the end-user. You have strong opinions about what makes a great developer experience.
-
You have experience building developer-facing products, APIs, SDKs, or CLIs.
-
You are proficient in one or more modern programming languages such as Go, Python, Ruby, or JavaScript and hands-on experience with LLM models.
-
Proven track record of deploying and maintaining ML services in production environments is a strong plus.
-
Solid understanding of API design, developer tooling, software architecture, data structures, and algorithms.
-
LLMops/MLops experience is a strong plus, especially in developer-facing products.
-
Experience building or supporting developer platforms, APIs, or sandbox environments is highly desirable.
Soft Skills / Personal Characteristics
-
Excellent written and verbal communication skills in English.
-
Collaborative team player with a passion for empowering developers and improving developer experience.
-
Adaptable, proactive, and creative—comfortable working in a dynamic, startup-like environment.
-
Strong problem-solving skills and a continuous improvement mindset.
(REQ ID: 2428)
Ready to apply?
Apply to Workato
Software Engineer - Developer Products (AI)
Share this job
About Workato
Workato delivers enterprise infrastructure for the agentic era, redefining iPaaS and helping enterprises unify data, applications, processes, and AI into a single, governed platform. A leader in Enterprise MCP and trusted by 50% of the Fortune 500, Workato’s cloud-native architecture connects every application, data source, and process to power real-time orchestration at scale. With enterprise-grade security and continuous innovation at its core, Workato provides the trusted foundation for organizations to automate with confidence and operationalize AI across the business. To learn more, visit www.workato.com
Why join us?
Ultimately, Workato believes in fostering a flexible, trust-oriented culture that empowers everyone to take full ownership of their roles. We are driven by innovation and looking for team players who want to actively build our company.
But, we also believe in balancing productivity with self-care. That’s why we offer all of our employees a vibrant and dynamic work environment along with a multitude of benefits they can enjoy inside and outside of their work lives.
If this sounds right up your alley, please submit an application. We look forward to getting to know you!
Also, feel free to check out why:
-
Business Insider named us an “enterprise startup to bet your career on”
-
Forbes’ Cloud 100 recognized us as one of the top 100 private cloud companies in the world
-
Deloitte Tech Fast 500 ranked us as the 17th fastest growing tech company in the Bay Area, and 96th in North America
-
Quartz ranked us the #1 best company for remote workers
Responsibilities
We are seeking a product-minded Software Engineer to join our San Francisco team focused on building the next generation of developer products. This role is at the forefront of innovation, specifically creating tools and platforms for developers who are building LLM and Agentic applications. You will be instrumental in shaping the future of how developers interact with and build on top of Workato's ecosystem in the age of AI. You will collaborate closely with product, engineering, and developer relations teams to deliver robust, scalable, and intuitive services. This role requires a high technical bar, plus an emphasis on developer ergonomics, so we can deliver a delightful developer experience. You will also be responsible to:
-
Design, build, and maintain robust, scalable, and high-quality developer-facing products and APIs for LLM and Agentic application development.
-
Collaborate closely with product managers, designers, developer relations and other engineers to translate developer needs and product requirements into elegant technical solutions.
-
Write clean, maintainable, and well-tested code, and contribute to a high standard of engineering excellence within the team.
-
Implement and improve validation, monitoring, and observability for ML services within the sandbox environment.
-
Drive the full development lifecycle: from ideation and architecture to deployment and continuous improvement.
-
Continuously evaluate and optimize existing implementations for performance, scalability, and developer usability.
-
Identify and resolve bottlenecks, bugs, and technical challenges in a fast-paced, iterative environment.
-
Conduct code reviews and mentor team members to uphold high engineering standards.
-
Stay at the cutting edge of AI, LLMs, and developer tooling, bringing new ideas and technologies to the team.
Requirements
Qualifications / Experience / Technical Skills
-
Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or equivalent industry experience.
-
3+ years of experience of professional software development experience, with a proven track record of shipping high-quality products.
-
You are a product-minded engineer who thinks deeply about the end-user. You have strong opinions about what makes a great developer experience.
-
You have experience building developer-facing products, APIs, SDKs, or CLIs.
-
You are proficient in one or more modern programming languages such as Go, Python, Ruby, or JavaScript and hands-on experience with LLM models.
-
Proven track record of deploying and maintaining ML services in production environments is a strong plus.
-
Solid understanding of API design, developer tooling, software architecture, data structures, and algorithms.
-
LLMops/MLops experience is a strong plus, especially in developer-facing products.
-
Experience building or supporting developer platforms, APIs, or sandbox environments is highly desirable.
Soft Skills / Personal Characteristics
-
Excellent written and verbal communication skills in English.
-
Collaborative team player with a passion for empowering developers and improving developer experience.
-
Adaptable, proactive, and creative—comfortable working in a dynamic, startup-like environment.
-
Strong problem-solving skills and a continuous improvement mindset.
(REQ ID: 2242)
Ready to apply?
Apply to Workato
AI Solutions & Delivery Manager, Business Controls
Share this job
Employee Applicant Privacy Notice
Who we are:
Shape a brighter financial future with us.
Together with our members, we’re changing the way people think about and interact with personal finance.
We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world.
The Role:
We are seeking an experienced AI Solutions & Delivery Engineer to join our Business Controls Group (BCG) as a hands-on technical leader focused on applying Artificial Intelligence, including Generative AI and Agentic AI, to accelerate and elevate first line of defense (1LOD) risk and control operations.
The ideal candidate will possess a blend of business and technical savvy, a vision for what AI can unlock within a controls environment, and the drive to transform that vision into reality. You will be responsible for partnering with stakeholders across BCG: listening, facilitating, hands-on developing, and delivering prioritized AI solutions that augment and elevate the capabilities of our risk and controls professionals.
You will focus on building AI-powered solutions for specific BCG initiatives, including control testing, horizontal risk-related reporting, and other 1LOD process acceleration activities, and manage a portfolio of AI initiatives from ideation through production deployment. This role exists to increase the quality, velocity, and scalability of how our Business Controls teams execute their work.
You will also serve as technical lead for the Business Controls AI Engineering function, acting as a system-level thinker, designing, orchestrating, building, and deploying AI agents, tools, and enterprise data integrations for BCG and 1LOD risk management teams within the guardrails of SoFi’s governance framework.
What you’ll do:
AI Strategy & Solutions Delivery
-
Partner with BCG leadership to define the AI solutions vision and roadmap for 1LOD risk and controls, based on business use case prioritization and scorecard evaluation.
-
Identify and implement opportunities where AI can uplift risk and control processes and practices, with an initial focus on control testing velocity and business controls reporting.
-
Design, develop, and deploy AI-powered solutions (including LLM-based agents, automated evidence analysis, and intelligent workflow tools) that deliver measurable improvements to BCG operations.
-
Translate ambiguous, fast-evolving AI work into clear narratives, artifacts, and decision frameworks for senior and executive leaders.
-
Manage the end-to-end AI product lifecycle, from ideation and requirements gathering through development, testing, launch, and post-launch optimization.
Stakeholder Engagement & Enablement
-
Partner with Business Controls teams, risk professionals, technology teams, and other BCG stakeholders to drive development, adoption, and continuous improvement of AI solutions.
-
Enable risk professionals’ adoption of AI tools by providing training, documentation, and hands-on support to increase comfort and proficiency across the organization.
-
Partner with enterprise AI and platform engineering teams to ensure AI solutions are built in compliance with best practices, enterprise policies, and internal standards.
-
Contribute to the uplifting and upscaling of AI capabilities across BCG, assisting in the responsible adoption of best-in-class AI platforms within the organization.
Performance & Metrics
-
Define key performance indicators (KPIs) and metrics for AI solutions, monitor performance post-launch, and iterate based on data-driven insights.
-
Ensure AI solutions deliver measurable business value, including reductions in cycle time, improvements in testing coverage, and enhanced reporting accuracy.
-
Establish and maintain dashboards that communicate AI initiative progress, adoption, and impact to BCG leadership.
Governance, Risk & Compliance
-
Manage end-to-end Generative AI and Responsible AI governance for BCG solutions, including documentation, validation, monitoring, explainability, and adherence to internal policies and emerging AI regulations.
-
Demonstrate critical thinking and the ability to clearly articulate risks and dimension impact when evaluating AI use cases and deployments.
-
Ensure all AI solutions align with enterprise governance standards, regulatory expectations, and model risk management requirements.
Technical Leadership
-
Serve as technical lead for the Business Controls AI Engineering function.
-
Evaluate, select, and integrate AI/ML tools and platforms that best serve BCG’s operational needs.
-
Break ambiguous problems into clear, measurable components and define actionable AI development plans.
-
Demonstrate sound judgment when balancing innovation against risk in a regulated financial services environment.
What you’ll need:
-
8+ years of experience in risk management, controls, compliance, or technology roles, with at least 3+ years focused on AI/ML products, applied AI solutions, or AI-driven process transformation.
-
Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field (or equivalent work experience).
-
Demonstrated experience in ambiguous or emerging domains, including leadership in defining, launching, and scaling AI solutions that deliver significant business impact.
-
Proven experience working at a senior individual contributor level or equivalent in a regulated organization, preferably in financial services.
-
Strong understanding of the financial services industry, including 1LOD risk management, control testing, and business controls operations.
-
Hands-on experience with AI/ML concepts including LLMs, Generative AI, Agentic AI, supervised/unsupervised learning, model monitoring, and responsible AI practices.
-
Understanding of data governance, data pipelines, and MLOps principles.
-
Strong communication and executive stakeholder engagement skills, with the ability to explain complex ideas clearly to non-experts at different audience levels.
-
Experience with regulatory expectations, model governance, and risk management in a banking or financial services context.
-
Strategic thinker with a strong analytical and problem-solving mindset.
-
Rapid self-learner in unfamiliar domains with a bias toward action and delivery.
Nice to have:
-
Experience with Snowflake, dbt, or other modern data platform tools used in enterprise data environments.
-
Familiarity with LLM tooling, RAG systems, AI agent frameworks, or AI-assisted data workflows.
-
Financial services experience across domains such as Credit, Fraud, Collections, or Operational Risk.
-
Experience with GRC platforms and control testing methodologies.
-
Experience implementing AI governance frameworks at scale.
-
AWS experience (S3, Glue, Lambda) and infrastructure-as-code familiarity.
SoFi provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion (including religious dress and grooming practices), sex (including pregnancy, childbirth and related medical conditions, breastfeeding, and conditions related to breastfeeding), gender, gender identity, gender expression, national origin, ancestry, age (40 or over), physical or medical disability, medical condition, marital status, registered domestic partner status, sexual orientation, genetic information, military and/or veteran status, or any other basis prohibited by applicable state or federal law.
The Company hires the best qualified candidate for the job, without regard to protected characteristics.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
New York applicants: Notice of Employee Rights
SoFi is committed to an inclusive culture. As part of this commitment, SoFi offers reasonable accommodations to candidates with physical or mental disabilities. If you need accommodations to participate in the job application or interview process, please let your recruiter know or email accommodations@sofi.com.
Due to insurance coverage issues, we are unable to accommodate remote work from Hawaii or Alaska at this time.
Ready to apply?
Apply to SoFi
Principal Product Manager - Fraud, Risk & ML Platform
Share this job
Employee Applicant Privacy Notice
Who we are:
Shape a brighter financial future with us.
Together with our members, we’re changing the way people think about and interact with personal finance.
We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world.
The Role
At SoFi, we’re on a mission to help our members get their money right. We are seeking a Principal Product Manager to lead the strategy and roadmap for our Fraud, Risk & ML Platform. This platform is the unified foundation for event-driven decisioning, risk-based interdictions, real-time feature stores, and self-serve ML capabilities across the enterprise.
You will shape SoFi’s risk and ML future, transforming complex backend processes into a seamless, self-serve platform that powers real-time decisioning for every SoFi product. Your goal is to accelerate organizational adoption of machine learning and expedite business growth by simplifying the integration of complex risk defenses that protect our members and the business.
What You’ll Do
- Strategic Roadmap: Own the multi-year vision for the Fraud, Risk & ML Platform, focusing on self-serve onboarding, reliability at scale, and superior developer experience.
- The "Model Factory": Direct the MLOps lifecycle to reduce model time-to-market from months to weeks. You will enable teams to build, deploy, and monitor ML models at enterprise scale.
- Platform Integration: Partner with internal product teams to identify friction in platform adoption and build features that eliminate integration pain points.
- Stakeholder Alignment: Drive onboarding for Fraud, AML, and Policy Engine use cases by aligning with Fraud, Risk, Data Science, and Infrastructure stakeholders on usage patterns, signals, features, and treatments, and guide execution teams to successfully deliver on those goals.
- Platform-as-a-Service: Drive Developer Experience (DX) as a core product feature; define clean APIs, versioning, SLAs, and documentation to reduce critical-path dependencies.
- Governance & Scalability: Establish a federated extension model for custom events, features, challenges, & actions to enable safe extensibility and cross-product reuse.
- Metrics & Impact: Define and track success metrics, including time-to-onboard, model deployment velocity, decision quality (e.g. precision/recall/F1), step‑up completion/abandon rates, and platform reliability.
- Flex into adjacent fraud initiatives, helping cover the gray space between domain detection/prevention improvements and platform onboarding/utilization.
- Evangelism: Educate partner teams on platform capabilities to ensure SoFi is fully leveraging centralized infrastructure rather than building bespoke silos.
What You’ll Need
- 7+ years of Product Management experience: with a focus on platform, infrastructure, or developer-facing products
- Technical fluency: Deep familiarity with APIs, event-driven systems (sync/async), high-throughput data pipelines, ML lifecycle (training, features, deployment, monitoring), risk decisioning engines/workflows
- ML Infrastructure: Proven experience operationalizing models in production using tools like Snowflake, Flink/streaming, Kafka, or AWS/SageMaker
- Platform mindset: A strong bias for normalization and generic, self-serve capabilities over bespoke builds.
- Exceptional Communication & Evangelism: ability to translate complex risk policy, business goals, and technical constraints into precise platform requirements, while rallying teams around a clear, forward-looking platform roadmap and strategy.
- Adaptive leadership: team‑first, able to navigate the gray space between domain‑specific fraud detection and horizontal platform utilization
- Direct experience with fraud and risk detection and prevention challenges and techniques.
Nice to Have
- Experience with risk decisioning, rules engines, risk mitigations and step-up challenges.
- Experience in FinTech or highly regulated financial environments.
- Background in building or scaling Generative AI for task‑automating agents (agentic workflows)
- Direct experience partnering with Data Science and MLEs to productionalize real-time scoring.
SoFi provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion (including religious dress and grooming practices), sex (including pregnancy, childbirth and related medical conditions, breastfeeding, and conditions related to breastfeeding), gender, gender identity, gender expression, national origin, ancestry, age (40 or over), physical or medical disability, medical condition, marital status, registered domestic partner status, sexual orientation, genetic information, military and/or veteran status, or any other basis prohibited by applicable state or federal law.
The Company hires the best qualified candidate for the job, without regard to protected characteristics.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
New York applicants: Notice of Employee Rights
SoFi is committed to an inclusive culture. As part of this commitment, SoFi offers reasonable accommodations to candidates with physical or mental disabilities. If you need accommodations to participate in the job application or interview process, please let your recruiter know or email accommodations@sofi.com.
Due to insurance coverage issues, we are unable to accommodate remote work from Hawaii or Alaska at this time.
Ready to apply?
Apply to SoFi
We are looking for a passionate Senior Community Engineer to educate Pulumi's rapidly growing community on infrastructure as code best practices and how best to maximize use of the Pulumi platform to achieve success in building modern cloud and AI infrastructure. You will be a part of realizing a vision where every engineer, and every AI agent, can program the cloud.
In this role, you will communicate Pulumi's unique and innovative worldview and approach to the world of engineers and engage with users to solve complex problems, from multi-cloud Kubernetes to GPU training clusters and agentic infrastructure workflows, and create scale by sharing these solutions with software engineers globally.
In addition to engaging deeply with the community, you will also work closely with Pulumi's product and engineering teams (including the team behind Pulumi Neo, our AI agent for infrastructure) to ensure that the needs of the community are always served by the Pulumi platform.
At Pulumi you will be challenged, learn, teach, and collaborate with an elite team of great people.
While Pulumi is headquartered in Seattle, WA., we are dedicated to being a remote first company. This role will be located in San Francisco, CA.
In This Role You Will:
- Write blog posts or whitepapers that offer architectural guidance, analyze varying technological viewpoints, and illustrate patterns and concepts around infrastructure as code, including AI-native architectures, GPU orchestration, and agentic IaC workflows.
- Speak and perform demos at leading technical conferences across both the cloud-native and AI/ML ecosystems (KubeCon, AWS re:Invent, Microsoft Ignite, Google Cloud Next, PyTorch Conference, Ray Summit, MLOps World, and more).
- Build thought leadership for Pulumi around infrastructure as code, platform engineering, and the emerging discipline of AI infrastructure engineering.
- Champion Pulumi Neo and our MCP server to the community, showing developers how to combine Pulumi with AI coding tools (Claude Code, Codex, Cursor) and agent frameworks like Strands Agents SDK, Google ADK, and LangChain to ship real infrastructure faster.
- Teach the community how to configure and prompt AI coding agents (Claude Code, Codex, Cursor, Cline, and similar) so they consistently produce reliable, idiomatic, production-grade Pulumi code, including patterns for context engineering, MCP-based tool wiring, evaluation, and guardrails.
- Develop reference architectures and demos for AI/ML workloads on Pulumi: training clusters, inference platforms, vector databases, RAG pipelines, and multi-cloud foundation-model portability across AWS Bedrock, Azure AI Foundry, and Google Vertex AI.
- Create demos to be used in talks, blogs, social media, and community opportunities.
- Foster Pulumi community virtually and at regional meetups, including AI-focused and platform-engineering communities.
This role spans our entire open source platform, across many clouds (AWS, Azure, Google Cloud, and Kubernetes), supporting any number of industry standard languages (JavaScript, TypeScript, Python, Go, etc.), and scenarios (containers, serverless, AI/ML, and infrastructure). We can safely guarantee that you will always be learning something new!
We're Looking For Someone With:
- 3+ years in a software development environment.
- Bachelor's degree in Computer Science or equivalent a plus.
- Excellent written and verbal communication skills, with the ability to convey complex technical concepts clearly.
- Demonstrated experience delivering technical presentations and live demos that help developers understand and adopt new tools
- Ability to author assets such as blog articles, tutorials, and workshops.
- Strong interest in and preferably hands-on experience with AI/ML infrastructure—LLMs, agentic workflows, GPU workloads, MCP, and AI-assisted developer tooling
- Hands-on experience configuring AI coding agents (Claude Code, Codex, Cursor, or similar) to produce reliable, production-grade code in real engineering workflows.
- Familiarity with prompt and context engineering patterns, MCP server integration, evals, and guardrails that keep agent output trustworthy.
- Experience in one or more of the following technologies a plus:
- Languages: Go, JavaScript, TypeScript, Python, or C#
- Cloud Platforms: Docker, Kubernetes, Amazon Web Services, Microsoft Azure, Google Cloud Platform
- Foundation-model platforms: AWS Bedrock, Azure AI Foundry, Google Vertex AI, or open-source equivalents (vLLM, Ollama, llama.cpp).
- AI/ML infrastructure: NVIDIA GPU operators, Kubeflow, Ray, KServe, or similar
- Building with or integrating LLMs: function calling, MCP servers, and agent frameworks such as Strands Agents SDK, Google ADK, or LangChain
Compensation:
- Base Salary Hiring Range: $152,00 - $198,000
- All full time employee offers at Pulumi include base salary, bonus or variable, equity and benefits (details below).
Benefits & Perks at Pulumi:
Healthcare Coverage:
We offer comprehensive medical, dental, vision, and supplemental insurance at no cost to U.S. employees. Internationally, we comply with local healthcare requirements and provide regionally appropriate coverage.
Time Off:
Our unlimited PTO policy encourages balance and rest — and we require employees to take at least three weeks off annually, plus 13 U.S. holidays.
401(k):
U.S. employees are eligible for a 401(k) plan with an employer match to support long-term financial wellness.
Parental Leave:
We provide 20 weeks of paid leave for birthing parents or primary caregivers, and 16 weeks for non-birthing parents or secondary caregivers.
Remote-First Culture:
Pulumi has been fully remote since 2020, with teammates across 20+ U.S. states and 12+ countries. We support flexible work with asynchronous collaboration and an annual “work from anywhere” stipend.
Professional Development:
Every employee receives an annual learning and development budget to support growth, learning, and career goals.
Equity Ownership:
We believe in acting like owners. All employees receive equity and are empowered to think big, move fast, and build the future of cloud together.
Additional Support:
We offer a monthly wellness fund to support mental and physical well-being, and a quarterly happiness fund for team connection.
About Pulumi:
Pulumi is reimagining how teams build cloud software, enabling developers and infrastructure experts to work better together through a unique combination of programming languages, tools, and systems innovation.
Our flagship infrastructure as code technology is open source and our SaaS product, Pulumi Cloud, provides platform teams, secrets management, and cloud management capabilities, and more. We have pioneered leveraging AI across all of these areas with our LLM-powered Pulumi Copilot to push the boundaries of what's possible. At Pulumi, we dream big, in the pursuit of helping our customers out-innovate and win.
Founded in 2017 by industry veterans with over five decades of combined experience building developer platforms, Pulumi now has a global community of more than 350,000 members and serves over 3,250 customers. Despite our rapid growth, we're still only getting started, and are early in our mission to democratize the cloud. If you thrive in a fast-paced, high-performance, we want to work with you to accelerate Pulumi's impact.
At Pulumi, we don't just accept difference, we celebrate, support, and thrive on it for the benefit of our employees, our products, and our customers. Pulumi is proud to be an equal opportunity workplace and is committed to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. If you have a disability or special need that requires accommodation, please let us know.
Ready to apply?
Apply to Pulumi
Software Engineer II, ML Platform, tvScientific
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About Pinterest:
Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.
Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible.
At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.
Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.
About tvScientific
tvScientific is the first and only CTV advertising platform purpose-built for performance marketers. We leverage massive data and cutting-edge science to automate and optimize TV advertising to drive business outcomes. Our solution combines media buying, optimization, measurement, and attribution in one, efficient platform. Our platform is built by industry leaders with a long history in programmatic advertising, digital media, and ad verification who have now purpose-built a CTV performance platform advertisers can trust to grow their business.
We are looking for an ambitious Systems / Platform Engineer to join a team at the intersection of SRE and low-latency distributed systems. This team will help power Pinterest’s next generation of realtime ML and measurement infrastructure, with a focus on sub‑millisecond decisioning, high‑throughput data access, and tight integration with Pinterest’s core tech stack.
In this role, you’ll think about queries and RPCs in terms of syscalls, cache lines, and wire formats, and design systems that stay fast and predictable under load. You’ll help define and harden the foundation for our training and serving stack: from storage and indexing strategies, to streaming and fanout, to backpressure and failure handling across services and regions. You’ll work closely with software engineering, data infra, and SRE partners to ensure our systems are observable, debuggable, and operable in production.
If topics like IO scheduling and batching, lock‑free or low‑contention data structures, connection pooling, query planning, kernel and network tuning, on‑disk layout and indexing, circuit‑breaking, autoscaling, incident response, NixOS, Rust, and robust SLIs/SLOs sound interesting (even if it’s just a subset), this role gives you a chance to apply that expertise to business‑critical, high‑leverage infrastructure at Pinterest scale.
What you'll do:
- Scale the decision making process for tools for the tvScientific AI team, from our workflows to our training infrastructure to our Kubernetes deployments
- Improve the developer experience for the data science team
- Upgrade our observability tooling
- Make every deployment smooth as our infrastructure evolves.
What we're looking for:
- Deep understanding of Linux
- Excellent writing skills
- A systems-oriented mindset
- Experience in high-performance software (RTB, HFT, etc.)
- Software engineering experience + reliability (e.g. CI/CD) expertise
- Strong observability instincts
- Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputs
- Strong track record of critical evaluation and verification of AI-assisted work (e.g., testing, source-checking, data validation, peer review)
- High integrity and ownership: you protect sensitive data, avoid over-reliance on AI, and remain accountable for final decisions and deliverables
- Nice-To-Haves
- Reverse-engineering experience
- Terraform, EKS, or MLOps experience
- Python, Scala, or Zig experience
- NixOS experience
- Adtech or CTV experience
- Experience deploying a distributed system across multiple clouds
- Experience in hard real-time low-latency (<10 ms) environments
In-Office Requirement Statement:
- We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role.
Relocation Statement:
- This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
#LI-SM4
#LI-REMOTE
At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.
Information regarding the culture at Pinterest and benefits available for this position can be found here.
Our Commitment to Inclusion:
Ready to apply?
Apply to Pinterest
Sr. Software Engineer, Simulation, tvScientific
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About Pinterest:
Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.
Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible.
At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.
Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.
About tvScientific
tvScientific is the first and only CTV advertising platform purpose-built for performance marketers. We leverage massive data and cutting-edge science to automate and optimize TV advertising to drive business outcomes. Our solution combines media buying, optimization, measurement, and attribution in one, efficient platform. Our platform is built by industry leaders with a long history in programmatic advertising, digital media, and ad verification who have now purpose-built a CTV performance platform advertisers can trust to grow their business.
We are seeking a Sr. Software Engineer to build out our simulation and AI capabilities. You'll design and implement systems that model the CTV advertising ecosystem — auction dynamics, bidding strategies, campaign outcomes, and counterfactual scenarios — and develop AI-driven tools that accelerate how we build, test, and deploy ML systems.
What you’ll do:
- Design and build simulation environments that model CTV auction mechanics, inventory supply, and advertiser competition
- Develop counterfactual and what-if frameworks for evaluating bidding strategies, budget allocation, and pacing algorithms offline
- Build AI agents that explore strategy spaces, generate hypotheses, and automate experimentation within simulated environments
- Use simulation to de-risk ML model deployments — validate new bidding and optimization strategies before they touch live traffic
- Define the technical direction for simulation and AI infrastructure and mentor engineers on the team
What we’re looking for:
- Systems programming experience in Zig or similar (C, C++, Rust)
- Deep understanding of probabilistic modeling, stochastic processes, or agent-based simulation
- Hands-on experience with modern AI tools: LLMs, code generation, agentic workflows — and good judgment about when they help vs. when they don't
- Adtech experience: you understand RTB mechanics, and the dynamics of programmatic advertising
- Ability to translate business questions ("what happens if we change our bid strategy?") into rigorous simulation frameworks
- Clear written communication: you'll be defining new technical directions and need to bring others along
- Ownership: you scope, design, and ship systems end-to-end with minimal direction
- Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputs
- Strong track record of critical evaluation and verification of AI-assisted work (e.g., testing, source-checking, data validation, peer review)
- High integrity and ownership: you protect sensitive data, avoid over-reliance on AI, and remain accountable for final decisions and deliverables.
- Nice-to-Haves:
- Strong production Python skills and experience building simulation or modeling systems
- Causal inference — uplift modeling, synthetic controls, difference-in-differences, or incrementality testing
- Experience with discrete event simulation, Monte Carlo methods, or digital twins
- Reinforcement learning — using simulated environments for policy learning and evaluation
- Experience building agentic AI systems or multi-agent simulations
- Big data experience with Scala and Spark
- MLOps experience — model deployment, monitoring, and pipeline orchestration on AWS
In-Office Requirement Statement:
- We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role.
Relocation Statement:
- This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
#LI-SM4
#LI-REMOTE
At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.
Information regarding the culture at Pinterest and benefits available for this position can be found here.
Our Commitment to Inclusion:
Ready to apply?
Apply to Pinterest
Sr. Software Engineer, ML Platform, tvScientific
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About Pinterest:
Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.
Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible.
At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.
Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.
About tvScientific
tvScientific is the first and only CTV advertising platform purpose-built for performance marketers. We leverage massive data and cutting-edge science to automate and optimize TV advertising to drive business outcomes. Our solution combines media buying, optimization, measurement, and attribution in one, efficient platform. Our platform is built by industry leaders with a long history in programmatic advertising, digital media, and ad verification who have now purpose-built a CTV performance platform advertisers can trust to grow their business.
We are looking for an experienced ML Platform Engineer to join a team at the intersection of sysops, systems programming, architecture, and large-scale deployments. Our platform underpins tvScientific’s distributed real-time bidding agent and ML training system that together drive $100M+ in annual revenue, giving you the opportunity to work on some of the most business-critical infrastructure in the company.
As part of our team, you’ll think about datasets in terms of bytes, microseconds, and serialization formats, and help define the next generation of our training and serving stack. A flagship initiative for the coming year is building a Kubernetes + Ray backend for our model training pipelines, setting a new bar for scale and reliability. If topics like data locality, observability and anomaly detection, distributed databases, high-performance computing, array programming languages, data security, and reproducibility excite you (even if it’s just a subset), your expertise could play a key role in shaping tvScientific’s ML innovation in 2026 and beyond.
What You'll Do
- Scale the decisionmaking process for tools for the tvScientific AI team, from our workflows to our training infrastructure to our Kubernetes deployments
- Improve the developer experience for the data science team
- Upgrade our observability tooling
- Serve as a technical lead and mentor to the team
- Make every deployment smooth as our infrastructure evolves.
What We're Looking For
- Deep understanding of Linux
- Excellent writing skills
- A systems-oriented mindset
- Experience in high-performance software (RTB, HFT, etc.)
- Software engineering experience + reliability (e.g. CI/CD) expertise
- Strong observability instincts
- Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputs
- Strong track record of critical evaluation and verification of AI-assisted work (e.g., testing, source-checking, data validation, peer review)
- High integrity and ownership: you protect sensitive data, avoid over-reliance on AI, and remain accountable for final decisions and deliverables
- Nice-To-Haves
- Reverse-engineering experience
- Terraform, EKS, or MLOps experience
- Python, Scala, or Zig experience
- NixOS experience
- Adtech or CTV experience
- Experience deploying a distributed system across multiple clouds
- Experience in hard real-time low-latency (<10 ms) environments
In-Office Requirement Statement:
- We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role.
Relocation Statement:
- This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
#LI-SM4
#LI-REMOTE
At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.
Information regarding the culture at Pinterest and benefits available for this position can be found here.
Our Commitment to Inclusion:
Ready to apply?
Apply to Pinterest
Principal AI Engineer - Frontier Data
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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
The Role
We are looking for an elite engineer who builds like a hacker and communicates like a consultant. You will not just be building models in a notebook; you will be deployed to the front lines to build, architect, and ship end-to-end Agentic AI products directly for our most strategic customers.
This is a high-stakes role. You will face "tricky" customers who have vague requirements and high expectations. Your job is to translate their chaos into technical order, write production-grade code, and deploy autonomous agents that solve their actual business problems.
What You Will Do
- Build & Deploy (60%):
Design and ship full-stack AI applications. You own the pipeline from data ingestion to the LLM inference layer to the frontend interface.
Architect autonomous agentic workflows (using frameworks like LangChain, LangGraph, or custom implementations) that can reason, plan, and execute complex tasks.
Write robust, clean, and highly testable code (Python/Typescript). "It works on my machine" is not acceptable; it must work in the customer's restricted cloud environment.
Handle DevOps and MLOps constraints: Dockerizing agents, managing Kubernetes clusters, and optimizing inference latency.
- Customer Engineering (40%):
Serve as the technical face of the company for our most demanding accounts.
Navigate complex stakeholder environments. You will push back on unrealistic demands, clarify ambiguous requirements, and steer "tricky" customers toward technically feasible solutions without breaking rapport.
Translate technical constraints into business value for non-technical executives.
Generate high-quality data for our customers and ability to review the data generated by other experts. This is one of the most critical aspects of the role.
The "Must-Haves"
- Experience: 8–12 years of total engineering experience. You started as a strong Software Engineer and evolved into an AI specialist.
- Education: B.S./M.S. in Computer Science, Math, or Physics from a top-tier institution (IIT, MIT, Stanford, Harvard, Berkeley, CMU, or similar global top-ranking universities).
- Deep AI Fluency: You aren't just calling APIs. You understand RAG implementation nuances, vector database optimization, fine-tuning (LoRA/PEFT), and the architecture of agentic loops.
- Production Engineering: Experience with end-to-end deployment (AWS/GCP/Azure, CI/CD pipelines, Terraform, Docker).
The "Why You" (Soft Skills)
- Thick Skin & High EQ: You don't get flustered when a customer changes their mind for the third time in a week. You can hold your ground with a CTO and explain "why not" to a CEO.
- Extreme Attention to Detail: You catch the edge cases that others miss. You obsess over error handling, retry logic in agents, and data privacy.
- Grit: You enjoy the "messy" work of integrating legacy enterprise data just as much as prompting the latest model.
What will set you apart
- Public Code: A visible GitHub footprint is very helpful. We want to see your side projects, your contributions to open source, or your experiments with LLMs. Please include your GitHub link in your application.
Tech Stack
- Languages: Python (Expert).
- AI/Data (Expertise in all is not required): PyTorch, LangChain, LlamaIndex, Pinecone/Weaviate, OpenAI/Anthropic APIs, HuggingFace.
- Infra (Expertise in all is not required): Kubernetes, Terraform, AWS/GCP.
Compensation
232k-260k base + variable + equity
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 TuringSenior Product Manager - Data & Quality
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About Snorkel
At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data.
We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes between 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!
The Role
We are seeking a highly technical and strategic Senior Product Manager with deep AI/ML expertise to lead development across our agentic data systems, synthetic data systems, evaluations, and data-acceleration initiatives. This role is ideal for someone with a core ML/AI product background, strong familiarity with model development workflows, and demonstrated success delivering product experiences that improve the speed, quality, and scalability of data operations. You will work closely with Research, Engineering, Data Operations, and Design to define product vision, roadmap, and execution plans for intelligent workflow systems that optimize data pipelines, improve task quality, and enable faster and more efficient delivery of AI-ready datasets.
This is a highly cross-functional, technically deep IC role with broad surface area and significant impact. You will lead initiatives spanning multiple teams, balancing near-term execution with long-term platform evolution.
What You’ll Do
- Own the product vision, strategy, and roadmap for the task and Expert Contributor Evaluations product supporting internal and external platform users.
- Identify bottlenecks and lead cross-team efforts to improve overall quality and customer acceptance rate.
- Lead Evaluation products and tools across research, engineering, operations, and forward deployed engineers to drive excellence in product quality.
- Define, build, and set up continuous monitoring for performance metrics of Evaluations to improve their adaption, usage, and effectiveness.
- Own the strategy and execution of Expert Contributor Quality
- Build a recommendation system for optimal matching of ECs to tasks on the Snorkel Platform
- Work with cross-functional stakeholders to support enablement and adaptation initiatives of the Evaluations and Quality products
- Balance short-term delivery with long-term platform investments to support future growth.
Minimum Qualifications
- 5–7 years of experience as a Product Manager, with ownership of complex, cross-functional product areas.
- Educational background in computer science or related engineering practice
- Strong technical literacy across ML models, Gen AI concepts, LLM-based products, Agentic designs, evaluation, labeling strategies, and quality frameworks.
- Proven ability to drive deeply technical roadmaps end-to-end, from concept to launch.
- Ability to write clear PRDs, partner on research experimentation frameworks, and drive measurable outcomes.
- Experience building internal or platform-level products with complex workflows and multi-stakeholder environments.
- Proven ability to own end-to-end product experiences across multiple user personas.
- Strong analytical and problem-solving skills, with a track record of metrics-driven decision making.
- Excellent collaboration skills and experience partnering closely with Engineering, Research, and Operations teams.
Preferred Qualifications
- 5-7 years of experience as a Product Manager, including 3+ years focused on ML/AI products, MLOps, or data systems products.
- Experience with agent-based systems, generative AI, reinforcement learning, self-improving systems, or automated workforce/task routing platforms.
- Familiarity with LLMs, LLM Evaluations, human-in-the-loop systems, and synthetic data generation.
- Background in Machine Learning, Data Engineering, or related technical field
- Demonstrated ability to lead large, cross-team initiatives without formal authority.
Be Your Best at Snorkel
Joining Snorkel AI means becoming part of a company that has market proven solutions, robust funding, and is scaling rapidly—offering a unique combination of stability and the excitement of high growth. As a member of our team, you’ll have meaningful opportunities to shape priorities and initiatives, influence key strategic decisions, and directly impact our ongoing success. Whether you’re looking to deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions, you’re fully supported in building your career in an environment designed for growth, learning, and shared success.
Snorkel AI is proud to be an Equal Employment Opportunity employer and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. Snorkel AI embraces diversity and provides equal employment opportunities to all employees and applicants for employment. Snorkel AI prohibits discrimination and harassment of any type on the basis of 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 law. All employment is decided on the basis of qualifications, performance, merit, and business need.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
Ready to apply?
Apply to Snorkel AI
Partner 20, Applied ML, Engineer, ASG
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Founded in Silicon Valley in 2009 by Marc Andreessen and Ben Horowitz, Andreessen Horowitz (aka a16z) is a venture capital firm that backs bold entrepreneurs building the future through technology. We are stage agnostic. We invest in seed to venture to growth-stage technology companies, across AI, bio + healthcare, consumer, crypto, enterprise, fintech, games, and companies building toward American dynamism. a16z has $100B+ under management across multiple funds.
We’ve established a team that is defined by respect for the entrepreneur and the company-building process; we know what it’s like to be in the founder’s shoes. We’ve invested in companies like Anduril, Airbnb, Coinbase, Cursor, Databricks, Deel, Figma, GitHub, Roblox, SpaceX, and Stripe. Our team is at the forefront of new technology, helping founders and their companies impact and change the world.
The Role
You will join a team of highly autonomous, senior ICs developing both software capabilities for the firm’s investing and operating functions, and external-facing products for the firm’s partners, portfolio, and investors. This role specifically involves leading the technical strategy, architecture, and implementation of machine learning systems that power the firm’s internal and external-facing applications. You will be responsible for the entire model lifecycle, from feature engineering and training to large-scale, low-latency serving and robust MLOps infrastructure.
The Applied Software Group operates in the mode of an internal startup. We own an exceptionally tight feedback loop and take on requests from all corners of the firm. This is a high-visibility role that requires a clear architectural vision, strong software engineering fundamentals, exacting communication skills, and the ability to engage and educate our firm on the technology we are developing and shipping.
This role requires an in-office presence 2-3 days a week in our San Francisco, CA office.
To join our team, you should be excited to:
- Architect, build, and maintain scalable and reliable ML production pipelines (data, training, and inference)
- Collaborate with the Applied Software Group (ASG) team to integrate ML models into user-facing products serving the investing partnership and our operating teams
- Set and evolve MLOps standards for the team, including producibility, automated testing, CI/CD, observability, and model governance across the firm.
- Research and lead the implementation of model serving strategies (e.g., real-time APIs, batch processing) to meet strict latency and throughput requirements
- Drive the technical roadmap for core ML infrastructure, influencing platform choices and building cloud-native systems primarily on GCP.
- Operate with high autonomy, owning outcomes end-to-end, proactively identifying gaps, and raising the technical bar for the team.
- Set a high standard for code quality and system design, producing clear, principled, and extensible solutions that scale with the firm.
- Bring positive energy in every interaction with the team and foster inclusive collaboration
- Learn the inner workings of VC and work closely with the investing partnership
Minimum Qualifications
- 2+ years of professional experience as a Machine Learning Engineer or similar role.
- Strong mathematical intuition and problem-solving skills
- Expertise in Python and its statistical modeling ecosystem (e.g. NumPy, scikit-learn, etc.)
- Solid experience with major ML frameworks like PyTorch, TensorFlow, or JAX
- Proven experience deploying and managing ML models in a production environment using tools like Kubeflow, MLflow, Airflow, or TFX
- Strong understanding of containerization technologies (e.g., Docker, Kubernetes/GKE) as applied to ML serving
- Familiarity with cloud computing environments (preferably GCP), including data storage and compute services
- Low ego, high empathy, and the capacity to collaborate effectively with diverse teams
The anticipated salary range for this role is between $341,000 - $422,000, actual starting pay may vary based on a range of factors which can include experience, skills, and scope.
This role is eligible to participate in the a16z carry program and various discretionary bonus programs as well as benefit and perquisite plans including health, dental, vision, disability, life insurance, 401K plan, vacation, and sick leave.
a16z culture
- We do only first class business and only in a first class way
- We take a long view of relationships, because we are in the relationship business
- We believe in the future and bet the firm that way
- We are all different, we recognize that, and we win
- We celebrate the good times
- We do it for the team
- We play to win
At a16z we are always looking to hire the absolute best talent and recognize that diversity in our experiences and backgrounds is what makes us stronger. We hire candidates of any race, color, ancestry, religion, sex, national origin, sexual orientation, gender identity, age, marital or family status, disability, Veteran status, and any other status. These differences are what enables us to work towards the future we envision for ourselves, our portfolio companies, and the World.
Our organization participates in E-Verify. Click here to learn about E-Verify.
Andreessen Horowitz hereby reserves the right to make use of any unsolicited resumes received from outside recruiting agencies and / or individual recruiters without being responsible for payment of any fees asserted from the use of unsolicited resumes.
Ready to apply?
Apply to a16z
Software Engineer II, Simulation, tvScientific
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About Pinterest:
Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.
Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible.
At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.
Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.
About tvScientific
tvScientific is the first and only CTV advertising platform purpose-built for performance marketers. We leverage massive data and cutting-edge science to automate and optimize TV advertising to drive business outcomes. Our solution combines media buying, optimization, measurement, and attribution in one, efficient platform. Our platform is built by industry leaders with a long history in programmatic advertising, digital media, and ad verification who have now purpose-built a CTV performance platform advertisers can trust to grow their business.
We are seeking a Software Engineer to build out our simulation and AI capabilities. You'll design and implement systems that model the CTV advertising ecosystem — auction dynamics, bidding strategies, campaign outcomes, and counterfactual scenarios — and develop AI-driven tools that accelerate how we build, test, and deploy ML systems.
What you’ll do:
- Design and build simulation environments that model CTV auction mechanics, inventory supply, and advertiser competition
- Develop counterfactual and what-if frameworks for evaluating bidding strategies, budget allocation, and pacing algorithms offline
- Build AI agents that explore strategy spaces, generate hypotheses, and automate experimentation within simulated environments
- Use simulation to de-risk ML model deployments — validate new bidding and optimization strategies before they touch live traffic
- Define the technical direction for simulation and AI infrastructure and mentor engineers on the team
What we’re looking for:
- Systems programming experience in Zig or similar (C, C++, Rust)
- Deep understanding of probabilistic modeling, stochastic processes, or agent-based simulation
- Hands-on experience with modern AI tools: LLMs, code generation, agentic workflows — and good judgment about when they help vs. when they don't
- Adtech experience: you understand RTB mechanics, and the dynamics of programmatic advertising
- Ability to translate business questions ("what happens if we change our bid strategy?") into rigorous simulation frameworks
- Clear written communication: you'll be defining new technical directions and need to bring others along
- Ownership: you scope, design, and ship systems end-to-end with minimal direction
- Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputs
- Strong track record of critical evaluation and verification of AI-assisted work (e.g., testing, source-checking, data validation, peer review)
- High integrity and ownership: you protect sensitive data, avoid over-reliance on AI, and remain accountable for final decisions and deliverables.
- Nice-to-Haves:
- Strong production Python skills and experience building simulation or modeling systems
- Causal inference — uplift modeling, synthetic controls, difference-in-differences, or incrementality testing
- Experience with discrete event simulation, Monte Carlo methods, or digital twins
- Reinforcement learning — using simulated environments for policy learning and evaluation
- Experience building agentic AI systems or multi-agent simulations
- Big data experience with Scala and Spark
- MLOps experience — model deployment, monitoring, and pipeline orchestration on AWS
In-Office Requirement Statement:
- We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role.
Relocation Statement:
- This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
#LI-SM4
#LI-REMOTE
At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.
Information regarding the culture at Pinterest and benefits available for this position can be found here.
Our Commitment to Inclusion:
Ready to apply?
Apply to Pinterest
AI/ML Research Engineer
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Position
Manifold Bio is seeking a talented Machine Learning Research Engineer to join our growing AI team. You will work closely with our research scientists to implement, scale, and optimize machine learning systems that power our de novo antibody design platform and advance our protein design capabilities. Your efforts will contribute to building production-ready ML infrastructure that enables breakthrough discoveries in protein therapeutics. You will be expected to take ownership of engineering challenges in our ML pipeline, from data processing and model training to deployment and monitoring, while collaborating closely with our research team to translate cutting-edge ideas into robust, scalable systems.
This is an on-site role and can be based in either Boston, Massachusetts or San Francisco, California. Please only apply if you reside in these cities or are open to relocate.
Responsibilities
- Implement and optimize machine learning models for protein design
- Build and maintain scalable data processing pipelines for large-scale protein and molecular datasets
- Develop and deploy ML infrastructure for distributed training and inference across GPU clusters
- Collaborate with research scientists to translate experimental ML approaches into production-ready code
- Design and execute ML experiments with clear hypotheses and rigorous analysis
- Optimize model performance and computational efficiency for large-scale protein design tasks
- Build tools and utilities to support rapid prototyping and experimentation by the research team
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Machine Learning, Computational Biology, or related field
- 2+ years of hands-on experience with PyTorch and/or JAX for deep learning applications
- Strong proficiency in Python scientific computing stack (NumPy, Pandas, scikit-learn)
- Experience with distributed computing and GPU optimization techniques
- Familiarity with protein structure analysis, computational biology, or analogous problems in natural sciences
- Understanding of modern deep learning architectures and optimization techniques
- Experience implementing research papers or translating ML approaches to production systems
- Proficiency with version control (Git), testing frameworks, and software engineering best practices
- Strong problem-solving skills and ability to work independently on technical challenges
- Excellent written and verbal communication skills for cross-functional collaboration
Preferred Qualifications
- Experience training LLMs or diffusion generative models
- Knowledge of cloud computing platforms (AWS, GCP) and containerization (Docker, Kubernetes)
- Background in computational biology, bioinformatics, or structural biology
- Experience with large-scale data engineering and ETL pipelines
- Familiarity with MLOps practices and model deployment frameworks
This Role Might Be Perfect For You If
You are passionate about leveraging state of the art machine learning approaches to solve challenging disease areas
- You enjoy translating research ideas into high impact, productionized, scalable code
- You have rich AI/ML experience and are looking to pivot into biotech
If you're excited to build scalable ML systems that revolutionize protein therapeutic discovery, please reach out to careers@manifold.bio.
Base Salary Range: $140,000-225,000
This reflects the typical offer range for this role, based on experience, role scope, and internal equity. Final compensation decisions are made using a consistent leveling framework and consider the candidate’s experience, interview performance, and expected impact.
This role is eligible for:
- Annual performance-based target bonus
- Stock options
- Comprehensive medical, dental, and vision coverage
- 401(k) plan
- Flexible paid time off and holidays
- Perks including on-site gym, onsite lunch, and commuter support
Our compensation ranges are reviewed annually to ensure alignment with market trends and internal equity.
We value different experiences and ways of thinking and believe the most talented teams are built by bringing together people of diverse cultures, genders, and backgrounds.
Ready to apply?
Apply to Manifold Bio
At Anaplan, we are a team of innovators focused on optimizing business decision-making through our leading AI-infused scenario planning and analysis platform so our customers can outpace their competition and the market.
What unites Anaplanners across teams and geographies is our collective commitment to our customers’ success and to our Winning Culture.
Our customers rank among the who’s who in the Fortune 50. Coca-Cola, LinkedIn, Adobe, LVMH and Bayer are just a few of the 2,400+ global companies who rely on our best-in-class platform.
Our Winning Culture is the engine that drives our teams of innovators. We champion diversity of thought and ideas, we behave like leaders regardless of title, we are committed to achieving ambitious goals, and we love celebrating our wins – big and small.
Supported by operating principles of being strategy-led, values-based and disciplined in execution, you’ll be inspired, connected, developed and rewarded here. Everything that makes you unique is welcome; join us and let’s build what’s next - together!
ABOUT THE ROLE
This role sits within Anaplan's IT Customer Experience organization and is focused on transforming how Anaplan employees work. You will design, build, and scale AI tools, agents, and capabilities that drive productivity, smarter decision-making, and operational efficiency across our global workforce.
Anaplan is building its Enterprise AI Center of Excellence (COE) — a one-stop shop for all internal AI at Anaplan — and is looking for an AI Principal Architect to lead it from a technical standpoint. This is a senior, newly created role at the intersection of hands-on enterprise AI engineering, internal system architecture, technical leadership, and workforce enablement.
The AI Principal Architect will own the technical vision for Anaplan's internal AI — designing the reference architecture for LLMs, agentic AI, and Gemini Enterprise; setting engineering standards; evaluating emerging platforms; and ensuring every employee-facing initiative is built with rigor, scalability, and responsible design.
This role carries a hybrid profile: deep individual technical contribution combined with team leadership influence. You will mentor engineers, guide architectural decisions, serve as the primary technical escalation point, and contribute a forward-looking perspective to the 2–3 year AI technology roadmap — without necessarily holding formal management authority over all contributors.
You will report directly to the Director, IT Customer Experience, who co-leads the Enterprise AI COE alongside the Financial Flexibility Lead and a GTM Champion as a 3-in-a-box. You will collaborate closely with Technical/Engineering teams (dotted-line, for agent development and delivery) and the Transformation & Financial Flexibility team (to identify AI-driven cost-saving opportunities).
KEY RESPONSIBILITIES
Reference Architecture & Enterprise AI Engineering
- Own and publish the reference architecture for Anaplan's internal AI — covering LLMs, agentic AI frameworks, Gemini Enterprise integrations, and data pipelines.
- Architect end-to-end internal enterprise AI solutions designed for the scale, security, and reliability requirements of a global workforce.
- Set and enforce AI engineering standards, coding practices, code review processes, and technical guardrails across all internal AI projects.
- Lead hands-on technical design reviews and guide implementation decisions from intake through production deployment.
- Evaluate, select, and onboard new enterprise AI platforms and tools — providing technical recommendations grounded in internal workforce needs.
- Design the LLM abstraction layer and multi-model strategy to optimize cost, performance, and flexibility.
- Own technical debt management, system observability, and scalability planning for Anaplan's internal AI systems.
AI Platform Governance & Enablement
- Define and maintain technical evaluation criteria for the AI intake process — assessing feasibility, build complexity, security risk, and integration requirements for employee-facing tools.
- Ensure all internal AI initiatives pass engineering, security, compliance, and responsible AI review before development begins.
- Maintain enterprise AI technical policies, engineering standards, and responsible AI guardrails in partnership with Security and Compliance.
- Translate approved internal use cases into clear technical specifications and hand off to engineering teams with full architectural context.
- Define enterprise AI data layer and integration architecture across core systems (Salesforce, ServiceNow, Gainsight, Workday).
- Integrate with ServiceNow AI Control Tower to track all AI use cases, agents, and realized business value.
- Implement human-in-the-loop, explainability, and auditability frameworks for all decision-impacting AI systems.
- Partner with Finance to define and measure AI-driven ROI, ensuring alignment with enterprise value targets.
- Establish full lifecycle management for AI agents, including monitoring, feedback loops, and continuous improvement.
Technical Team Leadership
- Provide technical direction, coaching, and mentorship to engineers across the AI Governance & Enablement and AI Operations & Insights teams.
- Serve as the primary technical escalation point for complex internal AI delivery challenges and architecture decisions.
- Partner with Technical/Engineering teams (dotted-line) on agent architecture, build quality, and delivery timelines.
- Help define the technical bar for AI team hiring and contribute to onboarding and skills development programs.
- Foster a culture of engineering rigor, experimentation, and continuous improvement across the internal AI function.
AI Operations & Workforce Adoption
- Oversee the technical deployment and operationalization of AI agents and solutions, ensuring production readiness and stability for Anaplan employees.
- Drive Gemini Enterprise adoption and lead AI Friday sessions with genuine technical depth.
- Build and maintain engineering dashboards tracking internal AI system performance, adoption rates, and ROI metrics.
- Translate engineering decisions into executive-ready business value narratives for the Director, CIO, and Finance audiences.
Innovation, R&D & Emerging Technology
- Research and prototype emerging AI/ML techniques, large language models, agent frameworks, and enterprise tooling to identify internal productivity and cost-saving opportunities.
- Design and lead proof-of-concept pilots that validate novel internal use cases before committing to full engineering investment.
- Build and maintain the AI innovation pipeline — a living backlog of high-potential experiments.
- Contribute the technical perspective on where internal AI capabilities should be invested over the next 2–3 years, collaborating with the Director on the roadmap.
Cross-Functional Technical Partnership
- Work hand in hand with the Transformation & Financial Flexibility team to identify and technically validate AI-driven cost-saving opportunities in Anaplan's internal operations.
- Act as technical advisor and AI subject matter expert to business units identifying internal AI use cases.
- Support the 3-in-a-box COE co-leadership (IT, Finance, GTM) with technical analysis, architecture reviews, and feasibility assessments.
- Build trusted technical relationships across Engineering, Security, Compliance, Legal, and HR.
REQUIRED QUALIFICATIONS
- 7+ years of software or AI/ML engineering experience, with at least 3 years in a technical lead, staff engineer, or principal-level role — ideally with exposure to enterprise IT or internal tooling environments.
- Deep hands-on expertise across the AI/ML stack: LLMs, retrieval-augmented generation (RAG), agent frameworks, or MLOps pipelines — with experience in enterprise or workforce deployment contexts.
- Proven experience architecting and deploying enterprise-scale internal AI systems from design through production, including reliability, observability, and performance engineering.
- Proficiency in Python and enterprise cloud AI platforms (GCP Vertex AI, Azure AI, or AWS SageMaker) and AI orchestration tooling.
- Hands-on experience with Google Workspace AI and Gemini Enterprise, or equivalent enterprise AI platforms (e.g., Microsoft Copilot, OpenAI Enterprise).
- Demonstrated ability to provide technical leadership, mentorship, and architectural guidance to engineering teams without formal management authority.
- Ability to manage competing priorities, dependencies, and delivery timelines across multiple workstreams.
- Strong business acumen and communication skills — able to translate complex enterprise AI/ML concepts into business value narratives for C-level audiences.
- Experience in enterprise SaaS environments with complex stakeholder landscapes, security requirements, and compliance obligations.
PREFERRED QUALIFICATIONS
- Experience with AI governance frameworks, responsible AI principles, or enterprise AI policy and risk management for internal deployments.
- Familiarity with ServiceNow or similar ITSM platforms and integration patterns.
- Background in enterprise change management, internal AI enablement, or large-scale digital transformation programs.
- Experience working with cross-functional finance or business transformation teams on AI-driven cost optimization.
- Prior experience in an internal IT or enterprise technology function at a high-growth SaaS company.
- Enterprise technology function at a high-growth SaaS company.
Our Commitment to Diversity, Equity, Inclusion and Belonging (DEIB)
We believe attracting and retaining the best talent and fostering an inclusive culture strengthens our business. DEIB improves our workforce, enhances trust with our partners and customers, and drives business success. Build your career in a place where diversity, equity, inclusion and belonging aren’t just words on paper – this is what drives our innovation, it’s how we connect, and it contributes to what makes us a market leader. We believe in a hiring and working environment where all people are respected and valued, regardless of gender identity or expression, sexual orientation, religion, ethnicity, age, neurodiversity, disability status, citizenship, or any other aspect which makes people unique. We hire you for who you are, and we want you to bring your authentic self to work every day!
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, perform essential job functions, and receive equitable benefits and all privileges of employment. Please contact us to request accommodation.
Fraud Recruitment Disclaimer
It has come to our attention that fraudulent and fictitious job opportunities are being circulated on the Internet. Prospective candidates are being contacted by certain individuals, mainly through telephone calls, emails and correspondence, claiming they are representatives of Anaplan. The main purpose of these correspondences and announcements is to obtain privileged information from individuals.
Anaplan does not:
- Extend offers to candidates without an extensive interview process with a member of our recruitment team and a hiring manager via video or in person.
- Send job offers via email. All offers are first extended verbally by a member of our internal recruitment team whenever possible and then followed up via written communication.
All emails from Anaplan would come from an @anaplan.com email address. Should you have any doubts about the authenticity of an email, letter or telephone communication purportedly from, for, or on behalf of Anaplan, please send an email to people@anaplan.com before taking any further action in relation to the correspondence.
Ready to apply?
Apply to AnaplanAt Anaplan, we are a team of innovators focused on optimizing business decision-making through our leading AI-infused scenario planning and analysis platform so our customers can outpace their competition and the market.
What unites Anaplanners across teams and geographies is our collective commitment to our customers’ success and to our Winning Culture.
Our customers rank among the who’s who in the Fortune 50. Coca-Cola, LinkedIn, Adobe, LVMH and Bayer are just a few of the 2,400+ global companies who rely on our best-in-class platform.
Our Winning Culture is the engine that drives our teams of innovators. We champion diversity of thought and ideas, we behave like leaders regardless of title, we are committed to achieving ambitious goals, and we love celebrating our wins – big and small.
Supported by operating principles of being strategy-led, values-based and disciplined in execution, you’ll be inspired, connected, developed and rewarded here. Everything that makes you unique is welcome; join us and let’s build what’s next - together!
ABOUT THE ROLE
This role sits within Anaplan's IT Customer Experience organization and is focused on transforming how Anaplan employees work. You will design, build, and scale AI tools, agents, and capabilities that drive productivity, smarter decision-making, and operational efficiency across our global workforce.
Anaplan is building its Enterprise AI Center of Excellence (COE) — a one-stop shop for all internal AI at Anaplan — and is looking for an AI Principal Architect to lead it from a technical standpoint. This is a senior, newly created role at the intersection of hands-on enterprise AI engineering, internal system architecture, technical leadership, and workforce enablement.
The AI Principal Architect will own the technical vision for Anaplan's internal AI — designing the reference architecture for LLMs, agentic AI, and Gemini Enterprise; setting engineering standards; evaluating emerging platforms; and ensuring every employee-facing initiative is built with rigor, scalability, and responsible design.
This role carries a hybrid profile: deep individual technical contribution combined with team leadership influence. You will mentor engineers, guide architectural decisions, serve as the primary technical escalation point, and contribute a forward-looking perspective to the 2–3 year AI technology roadmap — without necessarily holding formal management authority over all contributors.
You will report directly to the Director, IT Customer Experience, who co-leads the Enterprise AI COE alongside the Financial Flexibility Lead and a GTM Champion as a 3-in-a-box. You will collaborate closely with Technical/Engineering teams (dotted-line, for agent development and delivery) and the Transformation & Financial Flexibility team (to identify AI-driven cost-saving opportunities).
KEY RESPONSIBILITIES
Reference Architecture & Enterprise AI Engineering
- Own and publish the reference architecture for Anaplan's internal AI — covering LLMs, agentic AI frameworks, Gemini Enterprise integrations, and data pipelines.
- Architect end-to-end internal enterprise AI solutions designed for the scale, security, and reliability requirements of a global workforce.
- Set and enforce AI engineering standards, coding practices, code review processes, and technical guardrails across all internal AI projects.
- Lead hands-on technical design reviews and guide implementation decisions from intake through production deployment.
- Evaluate, select, and onboard new enterprise AI platforms and tools — providing technical recommendations grounded in internal workforce needs.
- Design the LLM abstraction layer and multi-model strategy to optimize cost, performance, and flexibility.
- Own technical debt management, system observability, and scalability planning for Anaplan's internal AI systems.
AI Platform Governance & Enablement
- Define and maintain technical evaluation criteria for the AI intake process — assessing feasibility, build complexity, security risk, and integration requirements for employee-facing tools.
- Ensure all internal AI initiatives pass engineering, security, compliance, and responsible AI review before development begins.
- Maintain enterprise AI technical policies, engineering standards, and responsible AI guardrails in partnership with Security and Compliance.
- Translate approved internal use cases into clear technical specifications and hand off to engineering teams with full architectural context.
- Define enterprise AI data layer and integration architecture across core systems (Salesforce, ServiceNow, Gainsight, Workday).
- Integrate with ServiceNow AI Control Tower to track all AI use cases, agents, and realized business value.
- Implement human-in-the-loop, explainability, and auditability frameworks for all decision-impacting AI systems.
- Partner with Finance to define and measure AI-driven ROI, ensuring alignment with enterprise value targets.
- Establish full lifecycle management for AI agents, including monitoring, feedback loops, and continuous improvement.
Technical Team Leadership
- Provide technical direction, coaching, and mentorship to engineers across the AI Governance & Enablement and AI Operations & Insights teams.
- Serve as the primary technical escalation point for complex internal AI delivery challenges and architecture decisions.
- Partner with Technical/Engineering teams (dotted-line) on agent architecture, build quality, and delivery timelines.
- Help define the technical bar for AI team hiring and contribute to onboarding and skills development programs.
- Foster a culture of engineering rigor, experimentation, and continuous improvement across the internal AI function.
AI Operations & Workforce Adoption
- Oversee the technical deployment and operationalization of AI agents and solutions, ensuring production readiness and stability for Anaplan employees.
- Drive Gemini Enterprise adoption and lead AI Friday sessions with genuine technical depth.
- Build and maintain engineering dashboards tracking internal AI system performance, adoption rates, and ROI metrics.
- Translate engineering decisions into executive-ready business value narratives for the Director, CIO, and Finance audiences.
Innovation, R&D & Emerging Technology
- Research and prototype emerging AI/ML techniques, large language models, agent frameworks, and enterprise tooling to identify internal productivity and cost-saving opportunities.
- Design and lead proof-of-concept pilots that validate novel internal use cases before committing to full engineering investment.
- Build and maintain the AI innovation pipeline — a living backlog of high-potential experiments.
- Contribute the technical perspective on where internal AI capabilities should be invested over the next 2–3 years, collaborating with the Director on the roadmap.
Cross-Functional Technical Partnership
- Work hand in hand with the Transformation & Financial Flexibility team to identify and technically validate AI-driven cost-saving opportunities in Anaplan's internal operations.
- Act as technical advisor and AI subject matter expert to business units identifying internal AI use cases.
- Support the 3-in-a-box COE co-leadership (IT, Finance, GTM) with technical analysis, architecture reviews, and feasibility assessments.
- Build trusted technical relationships across Engineering, Security, Compliance, Legal, and HR.
REQUIRED QUALIFICATIONS
- 7+ years of software or AI/ML engineering experience, with at least 3 years in a technical lead, staff engineer, or principal-level role — ideally with exposure to enterprise IT or internal tooling environments.
- Deep hands-on expertise across the AI/ML stack: LLMs, retrieval-augmented generation (RAG), agent frameworks, or MLOps pipelines — with experience in enterprise or workforce deployment contexts.
- Proven experience architecting and deploying enterprise-scale internal AI systems from design through production, including reliability, observability, and performance engineering.
- Proficiency in Python and enterprise cloud AI platforms (GCP Vertex AI, Azure AI, or AWS SageMaker) and AI orchestration tooling.
- Hands-on experience with Google Workspace AI and Gemini Enterprise, or equivalent enterprise AI platforms (e.g., Microsoft Copilot, OpenAI Enterprise).
- Demonstrated ability to provide technical leadership, mentorship, and architectural guidance to engineering teams without formal management authority.
- Ability to manage competing priorities, dependencies, and delivery timelines across multiple workstreams.
- Strong business acumen and communication skills — able to translate complex enterprise AI/ML concepts into business value narratives for C-level audiences.
- Experience in enterprise SaaS environments with complex stakeholder landscapes, security requirements, and compliance obligations.
PREFERRED QUALIFICATIONS
- Experience with AI governance frameworks, responsible AI principles, or enterprise AI policy and risk management for internal deployments.
- Familiarity with ServiceNow or similar ITSM platforms and integration patterns.
- Background in enterprise change management, internal AI enablement, or large-scale digital transformation programs.
- Experience working with cross-functional finance or business transformation teams on AI-driven cost optimization.
- Prior experience in an internal IT or enterprise technology function at a high-growth SaaS company.
- Enterprise technology function at a high-growth SaaS company.
Our Commitment to Diversity, Equity, Inclusion and Belonging (DEIB)
We believe attracting and retaining the best talent and fostering an inclusive culture strengthens our business. DEIB improves our workforce, enhances trust with our partners and customers, and drives business success. Build your career in a place where diversity, equity, inclusion and belonging aren’t just words on paper – this is what drives our innovation, it’s how we connect, and it contributes to what makes us a market leader. We believe in a hiring and working environment where all people are respected and valued, regardless of gender identity or expression, sexual orientation, religion, ethnicity, age, neurodiversity, disability status, citizenship, or any other aspect which makes people unique. We hire you for who you are, and we want you to bring your authentic self to work every day!
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, perform essential job functions, and receive equitable benefits and all privileges of employment. Please contact us to request accommodation.
Fraud Recruitment Disclaimer
It has come to our attention that fraudulent and fictitious job opportunities are being circulated on the Internet. Prospective candidates are being contacted by certain individuals, mainly through telephone calls, emails and correspondence, claiming they are representatives of Anaplan. The main purpose of these correspondences and announcements is to obtain privileged information from individuals.
Anaplan does not:
- Extend offers to candidates without an extensive interview process with a member of our recruitment team and a hiring manager via video or in person.
- Send job offers via email. All offers are first extended verbally by a member of our internal recruitment team whenever possible and then followed up via written communication.
All emails from Anaplan would come from an @anaplan.com email address. Should you have any doubts about the authenticity of an email, letter or telephone communication purportedly from, for, or on behalf of Anaplan, please send an email to people@anaplan.com before taking any further action in relation to the correspondence.
Ready to apply?
Apply to AnaplanAt Anaplan, we are a team of innovators focused on optimizing business decision-making through our leading AI-infused scenario planning and analysis platform so our customers can outpace their competition and the market.
What unites Anaplanners across teams and geographies is our collective commitment to our customers’ success and to our Winning Culture.
Our customers rank among the who’s who in the Fortune 50. Coca-Cola, LinkedIn, Adobe, LVMH and Bayer are just a few of the 2,400+ global companies who rely on our best-in-class platform.
Our Winning Culture is the engine that drives our teams of innovators. We champion diversity of thought and ideas, we behave like leaders regardless of title, we are committed to achieving ambitious goals, and we love celebrating our wins – big and small.
Supported by operating principles of being strategy-led, values-based and disciplined in execution, you’ll be inspired, connected, developed and rewarded here. Everything that makes you unique is welcome; join us and let’s build what’s next - together!
ABOUT THE ROLE
This role sits within Anaplan's IT Customer Experience organization and is focused on transforming how Anaplan employees work. You will design, build, and scale AI tools, agents, and capabilities that drive productivity, smarter decision-making, and operational efficiency across our global workforce.
Anaplan is building its Enterprise AI Center of Excellence (COE) — a one-stop shop for all internal AI at Anaplan — and is looking for an AI Principal Architect to lead it from a technical standpoint. This is a senior, newly created role at the intersection of hands-on enterprise AI engineering, internal system architecture, technical leadership, and workforce enablement.
The AI Principal Architect will own the technical vision for Anaplan's internal AI — designing the reference architecture for LLMs, agentic AI, and Gemini Enterprise; setting engineering standards; evaluating emerging platforms; and ensuring every employee-facing initiative is built with rigor, scalability, and responsible design.
This role carries a hybrid profile: deep individual technical contribution combined with team leadership influence. You will mentor engineers, guide architectural decisions, serve as the primary technical escalation point, and contribute a forward-looking perspective to the 2–3 year AI technology roadmap — without necessarily holding formal management authority over all contributors.
You will report directly to the Director, IT Customer Experience, who co-leads the Enterprise AI COE alongside the Financial Flexibility Lead and a GTM Champion as a 3-in-a-box. You will collaborate closely with Technical/Engineering teams (dotted-line, for agent development and delivery) and the Transformation & Financial Flexibility team (to identify AI-driven cost-saving opportunities).
KEY RESPONSIBILITIES
Reference Architecture & Enterprise AI Engineering
- Own and publish the reference architecture for Anaplan's internal AI — covering LLMs, agentic AI frameworks, Gemini Enterprise integrations, and data pipelines.
- Architect end-to-end internal enterprise AI solutions designed for the scale, security, and reliability requirements of a global workforce.
- Set and enforce AI engineering standards, coding practices, code review processes, and technical guardrails across all internal AI projects.
- Lead hands-on technical design reviews and guide implementation decisions from intake through production deployment.
- Evaluate, select, and onboard new enterprise AI platforms and tools — providing technical recommendations grounded in internal workforce needs.
- Design the LLM abstraction layer and multi-model strategy to optimize cost, performance, and flexibility.
- Own technical debt management, system observability, and scalability planning for Anaplan's internal AI systems.
AI Platform Governance & Enablement
- Define and maintain technical evaluation criteria for the AI intake process — assessing feasibility, build complexity, security risk, and integration requirements for employee-facing tools.
- Ensure all internal AI initiatives pass engineering, security, compliance, and responsible AI review before development begins.
- Maintain enterprise AI technical policies, engineering standards, and responsible AI guardrails in partnership with Security and Compliance.
- Translate approved internal use cases into clear technical specifications and hand off to engineering teams with full architectural context.
- Define enterprise AI data layer and integration architecture across core systems (Salesforce, ServiceNow, Gainsight, Workday).
- Integrate with ServiceNow AI Control Tower to track all AI use cases, agents, and realized business value.
- Implement human-in-the-loop, explainability, and auditability frameworks for all decision-impacting AI systems.
- Partner with Finance to define and measure AI-driven ROI, ensuring alignment with enterprise value targets.
- Establish full lifecycle management for AI agents, including monitoring, feedback loops, and continuous improvement.
Technical Team Leadership
- Provide technical direction, coaching, and mentorship to engineers across the AI Governance & Enablement and AI Operations & Insights teams.
- Serve as the primary technical escalation point for complex internal AI delivery challenges and architecture decisions.
- Partner with Technical/Engineering teams (dotted-line) on agent architecture, build quality, and delivery timelines.
- Help define the technical bar for AI team hiring and contribute to onboarding and skills development programs.
- Foster a culture of engineering rigor, experimentation, and continuous improvement across the internal AI function.
AI Operations & Workforce Adoption
- Oversee the technical deployment and operationalization of AI agents and solutions, ensuring production readiness and stability for Anaplan employees.
- Drive Gemini Enterprise adoption and lead AI Friday sessions with genuine technical depth.
- Build and maintain engineering dashboards tracking internal AI system performance, adoption rates, and ROI metrics.
- Translate engineering decisions into executive-ready business value narratives for the Director, CIO, and Finance audiences.
Innovation, R&D & Emerging Technology
- Research and prototype emerging AI/ML techniques, large language models, agent frameworks, and enterprise tooling to identify internal productivity and cost-saving opportunities.
- Design and lead proof-of-concept pilots that validate novel internal use cases before committing to full engineering investment.
- Build and maintain the AI innovation pipeline — a living backlog of high-potential experiments.
- Contribute the technical perspective on where internal AI capabilities should be invested over the next 2–3 years, collaborating with the Director on the roadmap.
Cross-Functional Technical Partnership
- Work hand in hand with the Transformation & Financial Flexibility team to identify and technically validate AI-driven cost-saving opportunities in Anaplan's internal operations.
- Act as technical advisor and AI subject matter expert to business units identifying internal AI use cases.
- Support the 3-in-a-box COE co-leadership (IT, Finance, GTM) with technical analysis, architecture reviews, and feasibility assessments.
- Build trusted technical relationships across Engineering, Security, Compliance, Legal, and HR.
REQUIRED QUALIFICATIONS
- 7+ years of software or AI/ML engineering experience, with at least 3 years in a technical lead, staff engineer, or principal-level role — ideally with exposure to enterprise IT or internal tooling environments.
- Deep hands-on expertise across the AI/ML stack: LLMs, retrieval-augmented generation (RAG), agent frameworks, or MLOps pipelines — with experience in enterprise or workforce deployment contexts.
- Proven experience architecting and deploying enterprise-scale internal AI systems from design through production, including reliability, observability, and performance engineering.
- Proficiency in Python and enterprise cloud AI platforms (GCP Vertex AI, Azure AI, or AWS SageMaker) and AI orchestration tooling.
- Hands-on experience with Google Workspace AI and Gemini Enterprise, or equivalent enterprise AI platforms (e.g., Microsoft Copilot, OpenAI Enterprise).
- Demonstrated ability to provide technical leadership, mentorship, and architectural guidance to engineering teams without formal management authority.
- Ability to manage competing priorities, dependencies, and delivery timelines across multiple workstreams.
- Strong business acumen and communication skills — able to translate complex enterprise AI/ML concepts into business value narratives for C-level audiences.
- Experience in enterprise SaaS environments with complex stakeholder landscapes, security requirements, and compliance obligations.
PREFERRED QUALIFICATIONS
- Experience with AI governance frameworks, responsible AI principles, or enterprise AI policy and risk management for internal deployments.
- Familiarity with ServiceNow or similar ITSM platforms and integration patterns.
- Background in enterprise change management, internal AI enablement, or large-scale digital transformation programs.
- Experience working with cross-functional finance or business transformation teams on AI-driven cost optimization.
- Prior experience in an internal IT or enterprise technology function at a high-growth SaaS company.
- Enterprise technology function at a high-growth SaaS company.
Our Commitment to Diversity, Equity, Inclusion and Belonging (DEIB)
We believe attracting and retaining the best talent and fostering an inclusive culture strengthens our business. DEIB improves our workforce, enhances trust with our partners and customers, and drives business success. Build your career in a place where diversity, equity, inclusion and belonging aren’t just words on paper – this is what drives our innovation, it’s how we connect, and it contributes to what makes us a market leader. We believe in a hiring and working environment where all people are respected and valued, regardless of gender identity or expression, sexual orientation, religion, ethnicity, age, neurodiversity, disability status, citizenship, or any other aspect which makes people unique. We hire you for who you are, and we want you to bring your authentic self to work every day!
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, perform essential job functions, and receive equitable benefits and all privileges of employment. Please contact us to request accommodation.
Fraud Recruitment Disclaimer
It has come to our attention that fraudulent and fictitious job opportunities are being circulated on the Internet. Prospective candidates are being contacted by certain individuals, mainly through telephone calls, emails and correspondence, claiming they are representatives of Anaplan. The main purpose of these correspondences and announcements is to obtain privileged information from individuals.
Anaplan does not:
- Extend offers to candidates without an extensive interview process with a member of our recruitment team and a hiring manager via video or in person.
- Send job offers via email. All offers are first extended verbally by a member of our internal recruitment team whenever possible and then followed up via written communication.
All emails from Anaplan would come from an @anaplan.com email address. Should you have any doubts about the authenticity of an email, letter or telephone communication purportedly from, for, or on behalf of Anaplan, please send an email to people@anaplan.com before taking any further action in relation to the correspondence.
Ready to apply?
Apply to Anaplan
Staff Product Manager (Developer tools)
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About Workato
Workato delivers enterprise infrastructure for the agentic era, redefining iPaaS and helping enterprises unify data, applications, processes, and AI into a single, governed platform. A leader in Enterprise MCP and trusted by 50% of the Fortune 500, Workato’s cloud-native architecture connects every application, data source, and process to power real-time orchestration at scale. With enterprise-grade security and continuous innovation at its core, Workato provides the trusted foundation for organizations to automate with confidence and operationalize AI across the business. To learn more, visit www.workato.com
Why join us?
Ultimately, Workato believes in fostering a flexible, trust-oriented culture that empowers everyone to take full ownership of their roles. We are driven by innovation and looking for team players who want to actively build our company.
But, we also believe in balancing productivity with self-care. That’s why we offer all of our employees a vibrant and dynamic work environment along with a multitude of benefits they can enjoy inside and outside of their work lives.
If this sounds right up your alley, please submit an application. We look forward to getting to know you!
Also, feel free to check out why:
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Business Insider named us an “enterprise startup to bet your career on”
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Forbes’ Cloud 100 recognized us as one of the top 100 private cloud companies in the world
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Deloitte Tech Fast 500 ranked us as the 17th fastest growing tech company in the Bay Area, and 96th in North America
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Quartz ranked us the #1 best company for remote workers
We’re looking for a Staff Product Manager for Developer Platforms who doesn’t just ship features—but defines what should exist in the first place. This role owns the end-to-end experience for developers building on Workato: from first API call to production-scale agent systems.
This is not a roadmap execution role. You will define the platform strategy, make hard tradeoffs, and build a product that developers choose in a competitive market.
Responsibilities
We are seeking a strategic Staff Product Manager to lead our developer-facing products for LLM and Agentic applications. In this pivotal role, you will be the bridge between our developers, our business goals, and our engineering teams, driving the vision and execution of next-generation AI-powered automation and integration tools on the Workato platform.
You will be responsible for the entire product lifecycle, from identifying market opportunities and defining the product vision to working with engineering to deliver solutions that empower developers. This role requires someone who has successfully built and shipped developer products before, with a deep understanding of developer ergonomics and an instinct for what separates good developer tools from truly exceptional ones.
This is a critical role for someone with a proven track record in developer experience, a strong understanding of the AI landscape, and the ability to translate complex technical capabilities into tangible business value. You should know what great developer tools look and feel like because you've built them yourself. You will also be responsible to:
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Define and champion the product vision, strategy, and roadmap for Workato's AI and LLM-focused developer products.
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Partner closely with engineering, design, marketing, and sales to deliver exceptional AI products and drive go-to-market success.
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Build deep insights into developer workflows, needs, and pain points through direct customer engagement, user research, and community feedback.
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Transform developer insights and business requirements into actionable PRDs, user stories, and technical specifications.
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Own the product backlog and feature prioritization, making data-driven decisions that balance immediate developer needs with long-term platform vision.
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Lead competitive intelligence and market analysis to identify emerging trends and ensure Workato stays ahead in AI developer tooling.
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Champion the product vision both internally and externally, engaging with developer communities, conferences, and key technical stakeholders.
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Establish and monitor key product metrics including developer satisfaction, API adoption, and platform engagement to drive continuous improvement.
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Drive developer adoption metrics and optimize onboarding experiences to reduce time-to-first-value.
Requirements
Qualifications / Experience / Technical Skills
- 7+ years in product management, including owning a developer-facing product or platform end-to-end—from defining the vision to shipping and iterating
- Strong product instincts for developer platforms, with a clear point of view on what differentiates winning products (DX, capabilities, ecosystem, distribution)
- Experience driving adoption with external developers, including improving key stages of the funnel: discover → try → activate → scale
- Hands-on experience building or managing APIs, SDKs, CLIs, or extensibility frameworks, with an understanding of how these impact real developer workflows
- Demonstrated developer empathy, grounded in observing and improving real workflows (e.g., working with APIs, CI/CD, logs, IDEs)
- Comfortable going deep with engineering on system design and tradeoffs, including constraints, scalability, and abstraction decisions
- Familiarity with modern AI/LLM or agent-based development workflows (e.g., orchestration, prompt iteration, evaluation, observability)
- Awareness of how developer workflows are evolving (AI copilots, APIs-first development, faster iteration cycles), with a perspective on where things are headed
Nice to Have
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Hands-on experience building or using LLM-powered applications and familiarity with AI frameworks like LangChain, LlamaIndex, or similar.
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Experience with integration, automation, or MLOps platforms.
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Active participation in developer communities through writing, speaking, or open-source contributions.
Soft Skills / Personal Characteristics
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You are a strategic thinker who can connect technology with business impact and craft a compelling product narrative.
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You have excellent leadership and communication skills, with the ability to influence and align cross-functional teams.
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You are comfortable with ambiguity and rapid iteration, thriving in fast-paced, innovative environments.
(REQ ID: 2249)
Ready to apply?
Apply to Workato
AI Research Engineer, Search and Context
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About the role
Hex is an AI-powered platform for modern Data Science and Data Analytics workflows. AI Research Engineers at Hex partner with product teams to build industry-leading AI experiences such as the Notebook Agent. In the process, AI Engineers will run experiments, fine-tune models, deploy AI infrastructure, and build and maintain experimentation tooling.
The backbone of all of our AI experiences is providing relevant context to the agent. As an AI Research Engineer focused on our search and context architecture, you’ll be responsible for building out key components of our agentic platform, from agentic search and discovery subagents to high-scale, permissions-aware indexing systems.
If you’re a strong builder excited to bring these capabilities to thousands of users, come do it on the best Data Science platform around, with the best user context.
We are looking for a senior engineer (from an AI Eng, SWE or MLE background) eager to rapidly expand our capabilities in several greenfield applications. As one of our team’s early hires, you will work on a variety of initiatives including:
- Experimenting with new agentic techniques for search, discovery, and context management
- Designing and implementing the architecture for our scalable search and indexing pipelines
- Working at the cutting edge of production AI applications deployed to real customers
This type of ownership will provide incredible opportunities for personal and professional growth. You will have ample technical and team leadership opportunities, depending on your interests.
We aim to deliver AI capabilities that radically accelerate and augment the data science workflow – we’ve got an exciting roadmap and are willing to share more details during the process. We’re particularly interested in candidates who bring inspired excitement about what is possible in this space.
We'd love to hear from you if you have:
- Experience building and measuring high quality search and recommendation systems
- Experience getting AI/ML capabilities into production and serving real users
- A lot of enthusiasm for applications of AI to real business problems.
- Understanding of core MLOps/SW Architecture concepts for modern ML-based applications.
- You’re comfortable working in both Python & JS/TS – it’s okay if you’re only strong in one, but openness to both is important.
- Experimentalist mindset – understanding that quick iteration, and discerning critical thinking, can yield rapid progress on new challenges.
- Interest in the data space, and a love of shipping great products and building tools that empower end users to do more.
- Experience maintaining a high quality bar for design, correctness, and testing.
Our stack
Our product is a web-based notebook and app authoring platform. Our frontend is built with Typescript and React, using a combination of Apollo GraphQL and Redux for managing application state and data. On the backend, we also use Typescript to power an Express/Apollo GraphQL server that interacts with Postgres, Redis, and Kubernetes to manage our database and Python kernels. Our backend is tightly integrated with our infrastructure and CI/CD, where we use a combination of Terraform, Helm, and AWS to deploy and maintain our stack.
In addition to our unique culture, Hex proudly offers a competitive total rewards package, including but not limited to, market-benched salary & equity, comprehensive health benefits, and flexible paid time off.
The salary range for this role is: $225,000-$285,000
The salary range shown may be a reflection of additional factors such as geographical location and skill ranges/levels we’re open to. Placement in the salary range will be decided upon completion of the interview process, taking into account factors like leaving room for growth, internal fairness & parity, your demonstrated skills, and the depth of your experience. Our Recruiting team will be able to provide more details during the interview process.
By submitting an application the candidate consents to the use of their personal information in accordance with the Hex Privacy policy: https://learn.hex.tech/docs/trust/privacy-policy.
Ready to apply?
Apply to Hex Technologies
Senior Machine Learning Engineer, Fraud Detection
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About Crunchyroll
Founded by fans, Crunchyroll delivers the art and culture of anime to a passionate community. We super-serve over 100 million anime and manga fans across 200+ countries and territories, and help them connect with the stories and characters they crave. Whether that experience is online or in-person, streaming video, theatrical, games, merchandise, events and more, it’s powered by the anime content we all love.
Join our team, and help us shape the future of anime!
About the role
In the role of senior machine learning engineer, you will report to the director of data science and machine learning in the Center for Data and Insights, working from Los Angeles or San Francisco area in California.
In this Machine Learning Engineer role focused on Algorithm Development and End-to-End Production at our VOD streaming company, you will lead the creation and deployment of scalable ML models to detect account sharing fraud, drawing from user behavior data like geolocation, concurrent sessions, and device profiles. This position is essential for collaborating with data scientists, product analysts, and data engineers, translating research prototypes into production systems that enhance detection accuracy while minimizing user disruption, aligning with proven strategies from streaming giants to boost subscriber growth.
We work a hybrid schedule, in-office three days a week; Tuesday, Wednesday, Thursday.
Core Areas of Responsibility
- Design and implement machine learning algorithms, including anomaly detection models, to identify unauthorized account sharing in real-time.
- Develop end-to-end ML pipelines for data preprocessing, model training, evaluation, and deployment using cloud platforms.
- Optimize models for performance, scalability, and efficiency to handle high-volume streaming data.
- Integrate ML solutions with existing systems via APIs and establish monitoring for model drift and retraining.
- Collaborate on A/B testing and iteration to refine algorithms based on feedback and evolving evasion tactics.
About You
- Experience: You bring 5+ years of hands-on experience in ML engineering, with a track record in fraud or anomaly detection systems, ideally in online, consumer facing products and services.
- Technical Skills: Expert in Python and frameworks like TensorFlow, PyTorch, or XGBoost, with proficiency in MLOps tools such as MLflow, Docker, and cloud services like AWS SageMaker, Databricks MLFlow, etc. Experience with cloud computing infra and tooling such as AWS/GCP.
- Cross-Functional Collaborations: Experienced in working with data scientists, engineers, and product teams to deploy models that support business goals like revenue optimization.
- Communication Skills: Strong ability to document technical processes and explain algorithm decisions to diverse stakeholders for seamless integration.
- Education Background: Possess a master's degree in computer science, machine learning, or a related quantitative field, with certifications in cloud ML being a plus.
- Communication Skills: Excellent verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.
Educational Background: Graduate degree (MS or PhD) in Computer Science, Statistics, or a related field.
About the Team
Our team is composed of passionate Machine Learning Engineers and Data Scientists who have already made a significant impact across our product offerings, content strategy, and user engagement metrics. As we expand our scope, our team is poised to become the cornerstone of innovation and growth across various business verticals within the company. We are dedicated to leveraging advanced machine learning techniques to continue transforming how users interact with and enjoy our offering of video contents and all other services.
Why you will love working at Crunchyroll
In addition to getting to work with fun, passionate and inspired colleagues, you will also enjoy the following benefits and perks:
- Receive a great compensation package including salary plus performance bonus earning potential, paid annually.
- Flexible time off policies allowing you to take the time you need to be your whole self.
- Generous medical, dental, vision, STD, LTD, and life insurance
- Health Saving Account HSA program
- Health care and dependent care FSA
- 401(k) plan, with employer match
- Employer paid commuter benefit
- Support program for new parents
- Pet insurance and some of our offices are pet friendly!
#LifeAtCrunchyroll #LI-Hybrid
About our Values
We want to be everything for someone rather than something for everyone and we do this by living and modeling our values in all that we do. We value
-
Courage. We believe that when we overcome fear, we enable our best selves.
-
Curiosity. We are curious, which is the gateway to empathy, inclusion, and understanding.
- Kaizen. We have a growth mindset committed to constant forward progress.
-
Service. We serve our community with humility, enabling joy and belonging for others.
Our commitment to diversity and inclusion
Our mission of helping people belong reflects our commitment to diversity & inclusion. It's just the way we do business.
We are an equal opportunity employer and value diversity at Crunchyroll. Pursuant to applicable law, we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Crunchyroll, LLC is an independently operated joint venture between US-based Sony Pictures Entertainment, and Japan's Aniplex, a subsidiary of Sony Music Entertainment (Japan) Inc., both subsidiaries of Tokyo-based Sony Group Corporation.
Questions about Crunchyroll’s hiring process? Please check out our Hiring FAQs: https://help.crunchyroll.com/hc/en-us/articles/360040471712-Crunchyroll-Hiring-FAQs
Please refer to our Candidate Privacy Policy for more information about how we process your personal information, and your data protection rights: https://tbcdn.talentbrew.com/company/22978/v1_0/docs/spe-jobs-privacy-policy-update-for-crpa-dec-21-22.pdf
Please beware of recent scams to online job seekers. Those applying to our job openings will only be contacted directly from @crunchyroll.com email account.
Ready to apply?
Apply to Crunchyroll, LLC
Senior Machine Learning Engineer, Recommendation and Personalization
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About Crunchyroll
Founded by fans, Crunchyroll delivers the art and culture of anime to a passionate community. We super-serve over 100 million anime and manga fans across 200+ countries and territories, and help them connect with the stories and characters they crave. Whether that experience is online or in-person, streaming video, theatrical, games, merchandise, events and more, it’s powered by the anime content we all love.
Join our team, and help us shape the future of anime!
About the role
In the role of Senior Machine Learning Engineer for Recommendation and Personalization, you will report to the Director of Data Science and Machine Learning in the Center for Data and Insights, working from Los Angeles or San Francisco area in California. You will lead the research, development, and test of advanced models, and work together with product and engineering partners to deliver tailored experiences for our fans across the anime ecosystem, including anime video recommendations, digital manga suggestions, merchandise personalization, anime-themed gaming, music, and more. This position will collaborate closely with scientists, engineers, product owners, to prototype innovative algorithms, evaluate their impact, and integrate them into production systems that drive user engagement, retention, discovery, and satisfaction.
We work a hybrid schedule, in-office three days a week; Tuesday, Wednesday, Thursday. This position can be based in our Los Angeles or San Francisco offices.
Core Areas of Responsibility
- Research, design, and implement machine learning algorithms for recommendation systems, including collaborative filtering, content-based models, and deep learning, and generative recommendation approaches to personalize content discoveries.
- Co-develop end-to-end ML pipelines for data ingestion, feature engineering, model training, evaluation, and deployment using scalable cloud platforms with engineers.
- Optimize models for accuracy, latency, and scalability to handle massive user interaction data from streaming and multi-platform, multi-domain experiences across the fandom.
- Integrate personalization solutions with other services, and implement monitoring for model performance, bias detection, and automated retraining.
- Collaborate on A/B testing, experimentation, and iterative improvements to refine recommendations based on user feedback and evolving content trends.
About You
We get excited about candidates, like you, because you have:
Experience: You bring 8+ years of hands-on experience in applied machine learning, with a proven track record in building recommendation systems or personalization engines, ideally in media, entertainment, or e-commerce platforms.
Technical Skills: Expert in Python and frameworks like TensorFlow, PyTorch, or Scikit-learn, with proficiency in MLOps tools such as MLflow, Docker, and cloud services like AWS SageMaker, Databricks, or similar. Experience with big data tools (e.g., Spark) and cloud infrastructure (e.g., AWS/GCP) for handling large-scale datasets.
Cross-Functional Collaborations: Experienced in partnering with data scientists and analysts, engineers, and product teams to deploy models that align with business objectives like increasing user retention and content consumption.
Communication Skills: Strong ability to document research findings, explain algorithmic choices, and present results to diverse stakeholders for effective adoption.
Educational Background: Graduate degree (MS or PhD) in Computer Science, Machine Learning, Statistics, or a related quantitative field, with publications or contributions in recommendation systems being a plus.
About the Team
Our team is composed of passionate Machine Learning Engineers and Data Scientists who have already made a significant impact across our product offerings, content strategy, and user engagement metrics. As we expand our scope, our team is poised to become the cornerstone of innovation and growth across various business verticals within the company. We are dedicated to leveraging advanced machine learning techniques to continue transforming how users interact with and enjoy our offering of video contents and all other services.
Why you will love working at Crunchyroll
In addition to getting to work with fun, passionate and inspired colleagues, you will also enjoy the following benefits and perks:
- Receive a great compensation package including salary plus performance bonus earning potential, paid annually.
- Flexible time off policies allowing you to take the time you need to be your whole self.
- Generous medical, dental, vision, STD, LTD, and life insurance
- Health Saving Account HSA program
- Health care and dependent care FSA
- 401(k) plan, with employer match
- Employer paid commuter benefit
- Support program for new parents
- Pet insurance and some of our offices are pet friendly!
#LifeAtCrunchyroll #LI-Hybrid
About our Values
We want to be everything for someone rather than something for everyone and we do this by living and modeling our values in all that we do. We value
-
Courage. We believe that when we overcome fear, we enable our best selves.
-
Curiosity. We are curious, which is the gateway to empathy, inclusion, and understanding.
- Kaizen. We have a growth mindset committed to constant forward progress.
-
Service. We serve our community with humility, enabling joy and belonging for others.
Our commitment to diversity and inclusion
Our mission of helping people belong reflects our commitment to diversity & inclusion. It's just the way we do business.
We are an equal opportunity employer and value diversity at Crunchyroll. Pursuant to applicable law, we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Crunchyroll, LLC is an independently operated joint venture between US-based Sony Pictures Entertainment, and Japan's Aniplex, a subsidiary of Sony Music Entertainment (Japan) Inc., both subsidiaries of Tokyo-based Sony Group Corporation.
Questions about Crunchyroll’s hiring process? Please check out our Hiring FAQs: https://help.crunchyroll.com/hc/en-us/articles/360040471712-Crunchyroll-Hiring-FAQs
Please refer to our Candidate Privacy Policy for more information about how we process your personal information, and your data protection rights: https://tbcdn.talentbrew.com/company/22978/v1_0/docs/spe-jobs-privacy-policy-update-for-crpa-dec-21-22.pdf
Please beware of recent scams to online job seekers. Those applying to our job openings will only be contacted directly from @crunchyroll.com email account.
Ready to apply?
Apply to Crunchyroll, LLC
Senior Applied Machine Learning Developer, Asset Intelligence
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MaintainX is the world’s leading mobile-first Asset and Work Intelligence platform for industrial and frontline environments. We’re a modern, IoT-enabled, cloud-based solution that powers maintenance, safety, and operations on physical equipment and facilities.
We help 12,000+ organizations—including Duracell, Univar Solutions, Titan America, McDonald’s, Brenntag, Cintas, Xylem, and Shell—achieve operational excellence and reliability at scale.
Following our $150 million Series D led by Bain Capital Ventures, Bessemer Ventures, August Capital, Amity Ventures, and Ridge Ventures, MaintainX has raised a total of $254 million, valuing the company at $2.5 billion.
As we enter our next phase of growth, we’re investing deeply in AI/ML, LLMs, and Industrial IoT to transform how frontline teams operate—predicting failures before they happen, automating workflows, and embedding intelligence into every asset and procedure.
The Role
We are seeking a highly skilled and motivated Senior Applied Machine Learning Developer to guide the technical direction and architecture of our Predictive Maintenance and Asset Intelligence initiatives.
You’ll combine deep ML expertise with strong software development and leadership skills—mentoring developers, scaling systems, and driving the roadmap for AI-enabled maintenance intelligence across thousands of industrial sites.
This role sits at the intersection of ML architecture, IoT data systems, and product impact, shaping the foundation for MaintainX’s predictive and generative AI strategy.
What you’ll do:
- Lead technical direction for predictive maintenance, anomaly detection, and LLM-powered intelligence across MaintainX products.
- Architect end-to-end ML systems—from data ingestion and feature development to model training, deployment, and monitoring.
- Mentor a growing team of ML and data developers, instilling best practices for experimentation, evaluation, and model lifecycle management.
- Partner with product and software development leaders to align AI roadmap with customer needs and business goals.
- Design reliable data and feedback loops that connect customer telemetry and operator feedback to model retraining.
- Drive performance optimization through techniques like quantization, distillation, and scalable inference serving.
- Work with LLM frameworks (LangChain, LlamaIndex, Hugging Face) to build reasoning systems and agentic workflows for asset and work intelligence.
- Ensure ML infrastructure meets production standards for latency, reliability, explainability, and security.
About you:
- 7+ years of experience in Machine Learning, Data Science, or Applied AI.
- Expertise in Python, and strong familiarity with PyTorch, TensorFlow, and cloud ML stacks (AWS, Databricks, or similar).
- Proven experience deploying production ML systems—not just prototypes—at scale.
- Strong background in LLMs, time-series modeling, and anomaly detection for real-world data.
- Demonstrated ability to lead architectural decisions, mentor developers, and collaborate across product, data, and platform teams.
- Knowledge of MLOps tooling (Docker, Kubernetes, Weights & Biases, MLflow, SageMaker).
- Advanced degree (MS/PhD) in Computer Science, Machine Learning, or related field preferred.
Bonus skills:
- Experience with OCR for extracting structured data from documents.
- Background in time-series modeling for predictive maintenance and anomaly detection.
- Familiarity with Industrial IoT systems (sensors, telemetry, edge computing).
- Experience applying reinforcement learning or agentic architectures for decision-making and control systems.
- Contributions to open-source ML frameworks or research in reliability, explainability, or digital twins.
What’s in it for you:
- Competitive salary and meaningful equity opportunities.
- Healthcare, dental, and vision coverage.
- 401(k) / RRSP enrollment program.
- Take what you need PTO.
- A high impact Culture:
- You’ll work with Smart, Humble Optimists across the globe.
- Meritocratic environment where ideas and outcomes are publicly celebrated.
About us:
We exist to make the lives of frontline and maintenance teams easier by building software that meets their real-world needs. Our product transforms how 80% of the global workforce—those who don’t sit behind a desk—manage their operations, assets, and teams.
MaintainX is committed to creating a diverse environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
Ready to apply?
Apply to MaintainX
Développeur(se) senior en Apprentissage automatique, Intelligence des actifs
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MaintainX est la première plateforme mobile au monde dédiée à la gestion des actifs et des tâches dans les environnements industriels et de première ligne. Nous proposons une solution moderne, basée sur l'IoT et le cloud, qui facilite la maintenance, la sécurité et l'exploitation des équipements et installations physiques.
Nous aidons plus de 12 000 organisations, dont Duracell, Univar Solutions, Titan America, McDonald's, Brenntag, Cintas, Xylem et Shell, à atteindre l'excellence opérationnelle et la fiabilité à grande échelle.
À la suite de notre série D de 150 millions de dollars menée par Bain Capital Ventures, Bessemer Ventures, August Capital, Amity Ventures et Ridge Ventures, MaintainX a levé un total de 254 millions de dollars, valorisant la société à 2,5 milliards de dollars.
Alors que nous entrons dans notre prochaine phase de croissance, nous investissons massivement dans l'IA/ML, les LLM et l'IoT industriel afin de transformer le mode de fonctionnement des équipes de première ligne, en prédisant les pannes avant qu'elles ne se produisent, en automatisant les flux de travail et en intégrant l'intelligence dans chaque actif et chaque procédure.
Le poste
Nous recherchons un développeur(se) senior en apprentissage automatique appliqué hautement qualifié et motivé pour orienter la direction technique et l'architecture de nos initiatives en matière de maintenance prédictive et d'intelligence des actifs.
Vous combinerez une expertise approfondie en apprentissage automatique avec de solides compétences en génie logiciel et en sens du leadership. Vous encadrerez des ingénieurs, développerez des systèmes et piloterez la feuille de route pour l'intelligence de maintenance basée sur l'IA sur des milliers de sites industriels.
Ce poste se situe à la croisée de l'architecture d'apprentissage automatique, des systèmes de données IoT et de l'impact des produits, et constitue le fondement de la stratégie d'IA prédictive et générative de MaintainX.
Ce que vous ferez:
- Diriger la direction technique pour la maintenance prédictive, la détection des anomalies et l'intelligence alimentée par LLM dans tous les produits MaintainX.
- Concevoir des systèmes ML de bout en bout, de l'ingestion des données et le développement des fonctionnalités à la formation, au déploiement et à la surveillance des modèles.
- Encadrer une équipe croissante de développeurs(ses) ML et de données, en inculquant les meilleures pratiques en matière d'expérimentation, d'évaluation et de gestion du cycle de vie des modèles.
- Collaborer avec les responsables des produits et de développement afin d'aligner la feuille de route de l'IA sur les besoins des clients et les objectifs commerciaux.
- Concevoir des boucles de données et de rétroaction fiables qui relient la télémétrie des clients et les commentaires des opérateurs au réentraînement des modèles.
- Optimiser les performances grâce à des techniques telles que la quantification, la distillation et le service d'inférence évolutif.
- Travailler avec des cadriciels LLM (LangChain, LlamaIndex, Hugging Face) pour créer des systèmes de raisonnement et des flux de travail agentifs pour l'intelligence des actifs et du travail.
- S'assurer que l'infrastructure ML répond aux normes de production en matière de latence, de fiabilité, d'explicabilité et de sécurité.
À propos de vous:
- Plus de 7 ans d'expérience dans le domaine de l'apprentissage automatique, de la science des données ou de l'IA appliquée.
- Expertise en Python et excellente maîtrise de PyTorch, TensorFlow et des piles ML cloud (AWS, Databricks ou similaires).
- Expérience avérée dans le déploiement à grande échelle de systèmes ML de production, et pas seulement de prototypes.
- Solide expérience en LLM, modélisation de séries chronologiques et détection d'anomalies pour les données du monde réel.
- Capacité avérée à diriger les décisions architecturales, à encadrer les développeurs(ses) et à collaborer avec les équipes chargées des produits, des données et des plateformes.
- Connaissance des outils MLOps (Docker, Kubernetes, Weights & Biases, MLflow, SageMaker).
- Diplôme de deuxième cycle (master/doctorat) en informatique, apprentissage automatique ou dans un domaine connexe préféré.
Une attention particulière est accordée aux candidats présentant les caractéristiques suivantes:
- Expérience avec l'OCR pour l'extraction de données structurées à partir de documents.
- Expérience dans la modélisation de séries chronologiques pour la maintenance prédictive et la détection d'anomalies.
- Connaissance des systèmes IoT industriels (capteurs, télémétrie, edge computing).
- Expérience dans l'application de l'apprentissage par renforcement ou des architectures agentuelles pour les systèmes de prise de décision et de contrôle.
- Contributions à des frameworks ML open source ou à la recherche dans les domaines de la fiabilité, de l'explicabilité ou des jumeaux numériques.
Quels sont les avantages pour vous?:
- Un salaire compétitif et des opportunités d'équité significatives.
- Couverture des soins de santé, des soins dentaires et de la vue.
- Programme d'inscription 401(k) / RRSP.
- Prenez les congés dont vous avez besoin.
- Une culture du travail :
- Vous travaillerez avec des personnes intelligentes, humbles et optimistes à travers le monde.
- Un environnement méritocratique où les idées et les résultats sont publiquement célébrés.
Qui sommes-nous:
MaintainX s'engage à créer un environnement diversifié. Tous les candidats qualifiés seront pris en considération pour un emploi sans considération de race, de couleur, de religion, de sexe, d'identité ou d'expression de genre, d'orientation sexuelle, d'origine nationale, de génétique, d'invalidité, d'âge ou de statut d'ancien combattant.
Ready to apply?
Apply to MaintainX
MLOps & Agentic Platform Engineer (AI Infrastructure)
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We are seeking a skilled MLOps & Agentic Platform Engineer. This role involves managing model registries, developing continuous training loops, and implementing A/B testing infrastructure. The ideal candidate will have a strong DevOps/MLOps background and be adept at deploying scalable microservices and building observability dashboards.
Responsibilities:
- Manage model registries, continuous training loops, and A/B testing infrastructure.
- Deploy agents as scalable microservices on Kubernetes.
- Build observability dashboards to track token usage, latency, and agent reasoning paths.
Qualifications:
- Strong DevOps/MLOps background (Kubernetes, Docker, Terraform).
- Experience with MLflow, Weights & Biases, or LangSmith.
- Knowledge of building scalable microservice architectures.
Ready to apply?
Apply to Hyphen Connect Limited
Location: San Francisco, CA (Hybrid)
What is Verse?
Energy markets are more volatile than ever. Rapid electrification and the rise of AI are driving unprecedented demand for power, while energy costs continue to rise across the globe. For the world’s largest energy buyers, managing energy has never been more complex or more critical.
Verse helps these organizations manage complex power portfolios with confidence by unifying energy data, planning, forecasting, and operations in one tool. Our Energy Cost Intelligence platform, Aria, brings together energy, finance, and operations teams with real-time, finance-ready intelligence—replacing spreadsheets and consultants with precision across the entire energy lifecycle. Built by an expert team of energy buyers, data scientists, and engineers, Verse enables faster, smarter energy decisions that reduce risk and lower energy costs.
The Role
Verse is seeking a Senior Data Scientist to join our Data Science Team. In this role, you will lead the development and deployment of advanced data-driven solutions across a range of applications, including electricity markets, renewable procurement, and Behind-The-Meter (BTM) battery storage. You will play a critical role in shaping our modeling and analytical data layer, leveraging machine learning techniques, supporting optimization modeling infrastructure, and developing scalable approaches to power Verse’s software offerings.
This position emphasizes strong technical depth in Python, machine learning, and analytical modeling, along with the ability to independently scope and execute complex projects end-to-end. Experience in electricity markets and energy systems is preferred.
Key Responsibilities
- Lead End-to-End Data Science Projects: Own and drive large projects from problem definition through scoping, modeling, validation, and production deployment. Translate business problems into scalable, high-impact modeling solutions with minimal oversight.
- Statistical & Machine Learning Modeling: Design, develop, and refine statistical and machine learning models (e.g., time series forecasting, probabilistic models, optimization-linked models) to support decision-making and enhance product capabilities.
- Analytics Engineering & Data Modeling: Perform complex data transformations and develop well-structured analytical data models. Translate business and analytical requirements into scalable, tested, and well-documented datasets, with an emphasis on dimensional modeling and reproducibility (e.g., dbt-style workflows).
- Software Development & Productionization: Write clean, efficient, and maintainable Python code. Contribute to integrating models into production systems and model deployment pipelines in a cloud-based environment.
- Exploratory Data Analysis & Insight Generation: Apply statistical methods and data exploration techniques to uncover insights, validate assumptions, and inform modeling approaches.
- Machine Learning and MLOps: Contribute to Verse’s machine learning modeling infrastructure to support scaling of ML models and improving reliability, monitoring, and performance in production.
- Cross-Functional Collaboration: Partner with product, engineering, and business stakeholders to ensure models and insights are aligned with user needs and effectively integrated into workflows.
- Technical Leadership: Mentor junior team members, contribute to best practices, and help shape the technical direction of modeling and analytics across the team.
What We're Looking For (Minimum Qualifications)
- Master’s degree or higher in Computer Science, Statistics, Engineering, Applied Mathematics, or a related quantitative field. A bachelor’s degree with significant relevant experience may be considered.
- 5+ years of professional experience in data science, machine learning, or a related field
- Proven track record of independently leading and delivering complex modeling or data science projects
- Experience deploying and maintaining models in production environments
- Strong Python expertise, including experience with scientific computing and ML libraries (e.g., NumPy, pandas, scikit-learn, PyTorch, TensorFlow)
- Strong foundation in statistical modeling and machine learning, including time series forecasting and model evaluation
- Hands-on experience in complex transformations, dimensional modeling, and translating analytical requirements into well-structured, tested, and documented models
What Will Make You Standout (Preferred Qualifications)
- Experience in energy, climate tech, or related domains (not required)
- Familiarity with optimization methods or operations research
- Experience with real-time or streaming data systems
- Prior experience mentoring or leading technical teams
- PhD in a quantitative field
What Makes Verse a Great Place to Work?
- Lead with Empathy: We lift each other up with humility and kindness, always putting colleagues and customers first
- Be Honest & Transparent: We prioritize effective communication to build trust with our team, customers, and stakeholders
- Move with Balance & Precision: We believe speed and perseverance must be accompanied by thoughtfulness and reflection
- Leave the World a Better Place: We are passionate about our mission, and we strive to create a sustainable world for future generations
Base Pay Range
$190,000 - $230,000
This is the estimated base salary range for this position, which does not include the value of benefits or a potential equity grant. A wide range of factors are considered in making compensation decisions, including but not limited to skill sets, market conditions, experience and training, licensure and certifications, and business and organizational needs.
Benefits and Employee Perks
- Competitive compensation and equity grant at a high-growth start up
- Comprehensive benefits package including medical, dental and vision insurance, and 401k
- Flexible hours and unlimited PTO
- Diverse and inclusive working environment
Verse is an equal opportunity employer. All applicants and employees are considered for hire, promotion, and compensation without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, marital or familial status.
Ready to apply?
Apply to Verse
Software Engineer Intern (ML Ops / Compute Migration)
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Heartflow is a medical technology company advancing the diagnosis and management of coronary artery disease, the #1 cause of death worldwide, using cutting-edge technology. The flagship product—an AI-driven, non-invasive cardiac test supported by the ACC/AHA Chest Pain Guidelines called the Heartflow FFRCT Analysis—provides a color-coded, 3D model of a patient’s coronary arteries indicating the impact blockages have on blood flow to the heart. Heartflow is the first AI-driven non-invasive integrated heart care solution across the CCTA pathway that helps clinicians identify stenoses in the coronary arteries (RoadMap™Analysis), assess coronary blood flow (FFRCT Analysis), and characterize and quantify coronary atherosclerosis (Plaque Analysis). Our pipeline of products is growing and so is our team; join us in helping to revolutionize precision heartcare.
Heartflow is a publicly traded company (HTFL) that has received international recognition for exceptional strides in healthcare innovation, is supported by medical societies around the world, cleared for use in the US, UK, Europe, Japan and Canada, and has been used for more than 500,000 patients worldwide.
We are looking for a motivated Software Engineering Intern to join our Machine Learning(ML) Engineering and MLOps team in our San Francisco office. In this role, you will work alongside senior engineers and research scientists on a scoped project contributing to HeartFlow's transition toward a cloud-native, unified ML pipeline. You will get hands-on exposure to cardiac AI technologies, software architecture, and validation approaches used to run algorithms at scale. You will be assigned to a project that spans across computational geometry, microservices, and inference pipeline architectures.
Required Qualifications
- Actively pursuing a Bachelor's Degree (rising juniors and seniors preferred) in Computer Science, Data Science, Mathematics, or Engineering
- Coursework or project experience in image processing or computational geometry.
- Exposure to algorithmic/scientific development and/or deep learning applications.
- Proficiency in Python with strong foundations in class design and object-oriented programming.
- Strong foundations in data structures and algorithms.
- Excellent communication and collaboration skills.
How You Stand Out
- Proficiency in modern C++ (C++11 and up)
- Exposure to cloud environments (AWS, GCP, Azure).
- Familiarity with containerization technologies (e.g., Docker).
- Exposure to build/package management tools (e.g., Conan, poetry/uv) or infrastructure-as-code frameworks (e.g., AWS CDK)
- Exposure to the use of Gen AI for software development.
- Previous internship experience in software development
A reasonable hourly rate estimate for this position is $45 to $60.
#LI-DNI
Ready to apply?
Apply to Heartflow