About the Team

The Counter Intrusion MSE team develops systems that provide force protection capabilities, monitoring the perimeter of secure areas, land or sea, for approaching people, vehicles, and vessels. We live in a world where security officers are increasingly overwhelmed by sensor data feeds. Our products leverage advanced sensor fusion and autonomy to seamlessly render activity in the environment to Lattice's common operating picture. This relieves operators of our system from a ton of burden and allows our customers to get more done with fewer personnel. Increasingly, Counter Intrusion MLEs are working on projects to bring customers' existing legacy security systems into the Lattice ecosystem. Key to this effort is building scalable software solutions so that we can service many customers without requiring bespoke software for each one. The Counter Intrusion team is responsible for the development, testing, deployment, and sustainment of our family of systems. We work closely with other teams from product, engineering, sales, logistics, operations, and mission success.

About the Role

We are looking for a Machine Learning Engineer to apply the latest research to solve our toughest problems. This role will be responsible for owning the whole machine learning stack for the Counter Intrusion team. You will design and train multi-sensor object detection models for perception on edge compute devices that push the boundaries of what's possible with our sensors. You will develop learning algorithms to optimize the behavior of autonomous systems. You will also be responsible for the end-to-end design, implementation, and performance of the ML stack, including the infrastructure for data collection and training. Your work will directly impact Anduril's ability to deliver cutting-edge defense technology, with the opportunity to identify and develop novel ML applications across our product portfolio.

Responsibilities

• Propose and prototype innovative solutions to solve real-world problems, leveraging the latest state-of-the-art techniques in the field
• Develop and maintain core ML pipelines
• Train and deploy deep learning models for real-time applications
• Collaborate cross-functionally with camera, systems and labeling teams
• Curate datasets for evaluating performance and comparing performance trends over time
• Provide technical mentorship to other junior ML engineers

Required Qualifications

• MS or PhD in Machine Learning, Robotics or Computer Science, with emphasis on Computer Vision
• BS in Computer Science, Machine Learning, Electrical Engineering, or related field
• 6+ years of experience developing, benchmarking and optimizing ML algorithms on large-scale datasets
• Strong Deep Learning and CV background
• Proficiency in C++ development in a Linux environment
• Experience with Python development and deep learning frameworks such as PyTorch, JAX and TensorFlow
• Experience deploying models with TensorRT and ONNX
• Optimize on-device inference and vision kernels across CPU/GPU/NPU
• Track record of developing and deploying CV models from R&D to production
• Experience writing and maintaining automated continuous integration tests
• Knowledge of system profiling and tuning for latency, memory and power efficiency
• Ability to conduct experiments, ablation studies and create highly detailed reports
• Eligible to obtain and maintain a U.S. Secret security clearance

Preferred Qualifications

• Experience in one or more of the following:
• Object Detection, Object Tracking, Instance Segmentation, Semantic Segmentation, Semantic Change Detection, Depth Estimation, Model Pruning and Compression
• Experience in one or more of the following:
• Visual Odometry, SLAM, Multi-view Geometry, Camera Models, RGB-D and LIDAR Sensor Fusion, Optical Flow
• Experience troubleshooting and analyzing remotely deployed software systems
• 1 year of experience in a technical leadership role

Recent Projects For This Role Include

What You'll Do

• C++ - writing clean, modular, C++ code
• Traditional computer vision algorithms
• Training deep learning networks using TensorFlow, Keras, or similar
• Data structures and architecture
• Must be willing and able to work onsite five days per week

What You Bring

• Bachelor's Degree in Computer Science, preferably with research experience 
• 2+ years of industry software engineering experience
• 1+ years of work or research experience with current neural net frameworks
• Mastery of at least one practical programming language
• Experience working in a agile team software development environment

US Employee Benefits

Verkada is committed to fostering a workplace environment that prioritizes the holistic health and wellbeing of our employees and their families by offering comprehensive wellness perks, benefits, and resources. Our benefits and perks programs include, but are not limited to:

• Healthcare programs that can be tailored to meet the personal health and financial well-being needs - Premiums are 100% covered for the employee under at least one plan and 80% for family premiums under all plans
• Nationwide medical, vision and dental coverage
• Health Saving Account (HSA) with annual employer contributions and Flexible Spending Account (FSA) with tax saving options
• Expanded mental health support
• Paid parental leave policy & fertility benefits
• Time off to relax and recharge through our paid holidays, firmwide extended holidays, flexible PTO and personal sick time
• Professional development stipend
• Fertility Stipend
• Wellness/fitness benefits
• Healthy lunches provided daily
• Commuter benefits

Additional Information

• We do sponsor and take over sponsorship of employment visas for this role. If we make you an offer, we will make every reasonable effort to get you a visa.

What we offer:

• Competitive compensation package including equity and annual bonuses
• Excellent Medical, Dental, and Vision plans through Kaiser Permanente, Cigna, and  MetLife (including a medical plan with infertility benefits)
• MetLife Legal Services, Identity & Fraud Protection, Hospital Indemnity Insurance, Accident Insurance, & Critical Illness Insurance
• Flexible PTO, 10 paid holidays, and generous parental leave policies
• Our office is centrally located in Mountain View, CA
• Office perks: dog-friendly, free catered lunch, a fully stocked kitchen, and free EV charging
• Long Term Disability, Short Term Disability, Life Insurance
• Wellbeing Benefits - Headspace through Cigna, Calm through Kaiser, One Medical, Gympass, Spring Health through Cigna, Rula (mental health navigation) 
• Fidelity 401(k)
• Commuter, FSA, Dependent Care FSA, HSA
• Various incentive programs (referral bonuses, patent bonuses, etc.)

Cresta is on a mission to turn every customer conversation into a competitive advantage by unlocking the true potential of the contact center. Our platform combines the best of AI and human intelligence to help contact centers discover customer insights and behavioral best practices, automate conversations and inefficient processes, and empower every team member to work smarter and faster. Born from the prestigious Stanford AI lab, Cresta's co-founder and chairman is Sebastian Thrun, the genius behind Google X, Waymo, Udacity, and more. Our leadership also includes CEO, Ping Wu, the co-founder of Google Contact Center AI and Vertex AI platform, and co-founder, Tim Shi, an early member of Open AI.

Join us on this thrilling journey to revolutionize the workforce with AI. The future of work is here, and it's at Cresta.

About the role:

We are looking for a motivated Data Science Intern to join our team. This role offers hands-on experience working with real-world data, building models, and supporting data-driven decision-making. You will collaborate with data scientists, engineers, and business stakeholders to solve meaningful problems.

What You'll Do :

• Collect, clean, and preprocess structured and unstructured data
• Perform exploratory data analysis to identify trends and insights
• Build and evaluate machine learning models under guidance
• Develop data visualizations and dashboards to communicate findings
• Assist in deploying models and monitoring their performance
• Work with large datasets using tools like Python, SQL, and cloud platforms
• Document processes, experiments, and results clearly
• Participate in team demos, feedback sessions, and learning opportunities.
• This role provides mentorship and exposure to customer-facing technical problem solving in a fast-moving AI/Product environment.

What We're Looking For:

• Enrolled in a Bachelor’s or Master’s degree program in Computer Science, Engineering, or a related field.
• Experience writing code in Python (or another general-purpose language).
• Strong interest in artificial intelligence, machine learning, or software engineering.
• Basic understanding of statistics and machine learning concepts
• Familiarity with libraries such as Pandas, NumPy, Scikit-learn, or TensorFlow/PyTorch
• Experience with SQL and working with databases
• Strong analytical and problem-solving skills
• Excellent communication skills and willingness to collaborate with teammates and customers.

Nice-to-Haves

• Experience with data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn)
• Familiarity with cloud platforms (AWS, GCP, or Azure)
• Knowledge of version control (Git)
• Exposure to big data tools (Spark, Hadoop) is a plus

This posting will be used to fill a newly-created role.

We have noticed a rise in recruiting impersonations across the industry, where scammers attempt to access candidates' personal and financial information through fake interviews and offers. All Cresta recruiting email communications will always come from the @cresta.ai domain. Any outreach claiming to be from Cresta via other sources should be ignored.  If you are uncertain whether you have been contacted by an official Cresta employee, reach out to recruiting@cresta.com.

Position Overview

Woolpert is hiring a Senior Software Engineer to join our dynamic Atlas Labs team supporting our Geospatial sector. This position reports to the Director of Product and AI. Atlas Labs oversees technology development for Woolpert’s Geospatial sector, including various types of AI model development, R&D, software infrastructure, and user-facing products.

We are unable to provide visa sponsorship for this position.  Applicants must already possess work authorization in the country the job is located.

What You Will Do:

• Contribute to the planning, research, design, architecture, development, and testing of Atlas Labs software features. You’ll write code daily, definitely in Python and possibly in C++ or JavaScript.
• Work as part of a cross-functional Scrum team with domain experts in AI/ML, Geospatial Data, Software Engineering, and GIS.
• Collaborate with internal and external users to ensure the correctness, quality, and availability of Atlas Labs software products.

What You Will Bring:

• Meaningful employment experience working on commercial software products
• Experience writing production code in Python, preferably dealing with large datasets
• Demonstrated experience or academic output in a relevant domain:
• Geospatial Data Processing
• Computer Vision
• AI & Machine Learning
• LiDAR
• Robotics/Self-Driving/Autonomy
• General familiarity with relevant technologies:
• Linux, Docker, and GitHub
• AI/ML frameworks (Tensorflow, Pytorch)
• Cloud platforms (Azure, AWS, Google)

Nice to Have:

• Familiarity with GIS applications like ESRI, QGIS, Google Earth
• Familiarity with orchestration frameworks like Kubernetes, AirFlow, MLFlow
• Programming experience in C++ or JavaScript
• Experience with Agile processes like Scrum

Benefits You Will Love

Certified as a Great Place to Work, Woolpert is one of the fastest-growing architecture, engineering, and geospatial companies in the world. With over 75 offices and countless projects around the globe, you’ll work on meaningful assignments that improve quality of life around the world. In addition to offering competitive pay, we provide employees with a robust set of unique benefits, including:

• Freedom to Work program: Set your own schedule and location (as appropriate).
• Principal program: Earn the opportunity to become an owner of the firm.
• Flexible paid time off/vacation: Take time off when it makes sense for you and your team.
• Career development: Explore a wide range of learning and growth opportunities within and across industries.
• Health, life, vision, and dental insurance: Cover all your medical bases.
• Paid sick time, retirement plan, fitness reimbursement, pet insurance, identity protection, technology stipend, employee assistance program, and more!

#LI-Hybrid

About the Role
We are seeking a Biomedical AI Engineer to design and deploy agentic AI systems that can reason over biomedical knowledge, plan multi-step analyses, and autonomously integrate diverse scientific data sources to accelerate therapeutic discovery.

This role goes beyond traditional LLM + RAG pipelines. You will build AI agents that can retrieve, synthesize, evaluate, and act on biomedical information across literature, omics datasets, and clinical records operating as intelligent systems embedded within discovery workflows.

Key Responsibilities

• Design and implement agentic AI architectures capable of multi-step reasoning, planning, and tool use in biomedical contexts.
• Develop LLM-based agents that dynamically retrieve, rank, and synthesize knowledge from scientific literature, knowledge graphs, omics datasets, and clinical data.
• Build memory and feedback mechanisms that allow agents to refine hypotheses, update context, and adapt to evolving data.
• Integrate external tools (analysis pipelines, simulation engines, statistical models, databases) into autonomous agent workflows.
• Architect scalable systems that combine structured and unstructured biomedical data within production-grade AI environments.
• Collaborate closely with computational biologists, translational scientists, and software engineers to embed agentic systems into real-world discovery pipelines.
• Evaluate robustness, reliability, and interpretability of autonomous systems in high-stakes biomedical settings.

Qualifications

• Degree in Computer Science, Machine Learning, Computational Biology, Biomedical Informatics, or related field.
• Strong hands-on experience with large language models, including fine-tuning, alignment, and structured prompting.
• Experience building agent-based systems or complex LLM orchestration frameworks (e.g., multi-agent systems, tool-using LLMs, planning modules).
• Proficiency in Python and modern ML frameworks (PyTorch, JAX, TensorFlow).
• Experience working with large-scale biomedical datasets (genomics, transcriptomics, clinical records, or scientific corpora).

Preferred

• Experience designing autonomous research assistants or AI systems that perform multi-step scientific reasoning.
• Familiarity with knowledge graphs, hybrid symbolic-neural systems, or multimodal foundation models.
• Understanding of privacy, security, and regulatory considerations in healthcare AI.

Compensation

We offer a competitive compensation and benefits package, seeking to provide an open, flexible, and friendly work environment to empower employees and provide them with a platform to develop their long-term careers. A Summary of Benefits is available for all applicants. We offer a competitive package that includes base salary, bonus, and equity. The base pay range for this position is expected to be $190,000 - $280,000 annually; however, the base pay offered may vary depending on the market, job-related knowledge, skills and capabilities, and experience.

Xaira Therapeutics an equal-opportunity employer. We believe that our strength is in our differences. Our goal to build a diverse and inclusive team began on day one, and it will never end.

TO ALL RECRUITMENT AGENCIES: Xaira Therapeutics does not accept agency resumes. Please do not forward resumes to our jobs alias or employees. Xaira Therapeutics is not responsible for any fees related to unsolicited resumes.

About the Role
We are looking for an AI Scientist to join our team at the intersection of machine learning and single-cell biology. This role will focus on developing and applying foundation models to large-scale perturb-seq and single-cell datasets to uncover new biological mechanisms and therapeutic opportunities. You will help design scalable ML architectures that can extract insight from high-dimensional perturbation data and integrate across multi-omic modalities.

Key Responsibilities

• Design, train, and refine foundation models tailored to perturb-seq and other single-cell datasets.
  Build pipelines for preprocessing, normalization, and integration of large-scale single-cell and perturbation data.
• Apply ML/AI approaches to model cellular responses to perturbations and identify causal biological insights.
• Collaborate with experimental biologists to align computational methods with experimental design and discovery goals.
• Develop multimodal integration approaches across transcriptomic, epigenomic, and proteomic single-cell readouts.
• Publish methods and results in top scientific journals and present at conferences.
  
  

Qualifications

• PhD or equivalent in Computational Biology, Computer Science, Bioinformatics, or related discipline.
• Strong expertise in single-cell data analysis, particularly perturb-seq 
• Hands-on experience with foundation models or large-scale self-supervised learning (e.g., transformers, variational autoencoders).
• Strong coding skills in Python, ML frameworks (PyTorch/TensorFlow), and single-cell analysis tools (Scanpy, Seurat).
• Experience in developing scalable ML methods for large biological datasets.
  
  

Preferred

• Background in causal inference, generative models, or representation learning for biological systems.
• Familiarity with multi-omics integration and cross-modal foundation models.
• Track record of impactful publications in computational biology, machine learning, or related fields.

Compensation

We offer a competitive compensation and benefits package, seeking to provide an open, flexible, and friendly work environment to empower employees and provide them with a platform to develop their long-term careers. A Summary of Benefits is available for all applicants. We offer a competitive package that includes base salary, bonus, and equity. The base pay range for this position is expected to be $150,000 - $240,000 annually; however, the base pay offered may vary depending on the market, job-related knowledge, skills and capabilities, and experience.

Xaira Therapeutics an equal-opportunity employer. We believe that our strength is in our differences. Our goal to build a diverse and inclusive team began on day one, and it will never end.

TO ALL RECRUITMENT AGENCIES: Xaira Therapeutics does not accept agency resumes. Please do not forward resumes to our jobs alias or employees. Xaira Therapeutics is not responsible for any fees related to unsolicited resumes.

Mission Summary:

Motional’s onboard autonomous driving system team works at the intersection of software engineering, machine learning, sensors, and hardware compute platforms to evolve Motional’s next-generation on-board autonomous driving system. As part of this team, the High Performance Compute Platform team is responsible for Motional’s current and next-generation onboard autonomous driving system. If you are a software engineer and love the idea of working on embedded AI hardware and software compute systems to create the next generation of autonomous vehicles, we would love to talk with you. We are hiring in a range of levels, from graduate engineers to Staff engineers.

What You'll Be Doing:

• Design and develop infrastructure software on various hardware platforms for applications such as vision processing, radar systems, safety monitoring, etc., to be run on self-driving vehicles.
• Design test harnesses for embedded software components and full systems
• Provide technical mentorship to engineers.
• Proactively work with cross-functional engineering teams to solve complex and interesting problems.
  
  

What We're Looking For:

• Experience with creating detailed requirements from use cases.
• Ability to lead a technical initiative, including breaking down work and guiding other engineers through execution.
• Experience writing software for embedded platforms in C and C++.
• Experience with Test-Driven Development (TDD).
• Experience working on embedded Linux / RTOSs.
• Experience working with networks (Ethernet, CAN etc.) and the common networking protocols.
• Experience with debugging on embedded platforms.
• Experience writing software in Python and experience doing automation with shell scripting.
• Experience working with ARM Cortex MCUs or Microprocessors.
  
  

Bonus Points (not required):

• Experience working with large data pipelines, and platforms that require deterministic execution.
• Experience using inter-system communication protocols such as I2C and SPI
• Experience deploying Machine Learning models.
• Experience working with GPUs.
• Experience working directly with the Linux kernel or Device Drivers.
• Experience with Simulation and Code Generation, and knowing when their use is appropriate.
• Experience working with Bazel.
• Experience integrating various sensors, including Cameras, IMUs, Radars, LIDARs.
• Experience with PyTorch, TensorFlow, ONNX, and/or other ML frameworks. 
  
  

We encourage a hybrid schedule with in-office time at one of our locations in Boston, Pittsburgh, or Las Vegas to support collaboration, or this role can be fully remote.

Mission Summary:

Motional’s onboard autonomous driving system team works at the intersection of software engineering, machine learning, sensors, and hardware compute platforms to evolve Motional’s next-generation on-board autonomous driving system. As part of this team, the High Performance Compute Platform team is responsible for Motional’s current and next-generation onboard autonomous driving system. If you are a software engineer and love the idea of working on embedded AI hardware and software compute systems to create the next generation of autonomous vehicles, we would love to talk with you. We are hiring in a range of levels, from graduate engineers to Staff engineers.

What You'll Be Doing:

• Design and develop infrastructure software on various hardware platforms for applications such as vision processing, radar systems, safety monitoring, etc., to be run on self-driving vehicles.
• Design test harnesses for embedded software components and full systems
• Provide technical mentorship to engineers.
• Proactively work with cross-functional engineering teams to solve complex and interesting problems.
  
  

What We're Looking For:

• Experience with creating detailed requirements from use cases.
• Ability to lead a technical initiative, including breaking down work and guiding other engineers through execution.
• Experience writing software for embedded platforms in C and C++.
• Experience with Test-Driven Development (TDD).
• Experience working on embedded Linux / RTOSs.
• Experience working with networks (Ethernet, CAN etc.) and the common networking protocols.
• Experience with debugging on embedded platforms.
• Experience writing software in Python and experience doing automation with shell scripting.
• Experience working with ARM Cortex MCUs or Microprocessors.
  
  

Bonus Points (not required):

• Experience working with large data pipelines, and platforms that require deterministic execution.
• Experience using inter-system communication protocols such as I2C and SPI
• Experience deploying Machine Learning models.
• Experience working with GPUs.
• Experience working directly with the Linux kernel or Device Drivers.
• Experience with Simulation and Code Generation, and knowing when their use is appropriate.
• Experience working with Bazel.
• Experience integrating various sensors, including Cameras, IMUs, Radars, LIDARs.
• Experience with PyTorch, TensorFlow, ONNX, and/or other ML frameworks. 
  
  

We encourage a hybrid schedule with in-office time at one of our locations in Boston, Pittsburgh, or Las Vegas to support collaboration, or this role can be fully remote.

Mission Summary:

Motional’s onboard autonomous driving system team works at the intersection of software engineering, machine learning, sensors, and hardware compute platforms to evolve Motional’s next-generation on-board autonomous driving system. As part of this team, the High Performance Compute Platform team is responsible for Motional’s current and next-generation onboard autonomous driving system. If you are a software engineer and love the idea of working on embedded AI hardware and software compute systems to create the next generation of autonomous vehicles, we would love to talk with you. We are hiring in a range of levels, from graduate engineers to Staff engineers.

What You'll Be Doing:

• Design and develop infrastructure software on various hardware platforms for applications such as vision processing, radar systems, safety monitoring, etc., to be run on self-driving vehicles.
• Design test harnesses for embedded software components and full systems
• Provide technical mentorship to engineers.
• Proactively work with cross-functional engineering teams to solve complex and interesting problems.
  
  

What We're Looking For:

• Experience with creating detailed requirements from use cases.
• Ability to lead a technical initiative, including breaking down work and guiding other engineers through execution.
• Experience writing software for embedded platforms in C and C++.
• Experience with Test-Driven Development (TDD).
• Experience working on embedded Linux / RTOSs.
• Experience working with networks (Ethernet, CAN etc.) and the common networking protocols.
• Experience with debugging on embedded platforms.
• Experience writing software in Python and experience doing automation with shell scripting.
• Experience working with ARM Cortex MCUs or Microprocessors.
  
  

Bonus Points (not required):

• Experience working with large data pipelines, and platforms that require deterministic execution.
• Experience using inter-system communication protocols such as I2C and SPI
• Experience deploying Machine Learning models.
• Experience working with GPUs.
• Experience working directly with the Linux kernel or Device Drivers.
• Experience with Simulation and Code Generation, and knowing when their use is appropriate.
• Experience working with Bazel.
• Experience integrating various sensors, including Cameras, IMUs, Radars, LIDARs.
• Experience with PyTorch, TensorFlow, ONNX, and/or other ML frameworks. 
  
  

We encourage a hybrid schedule with in-office time at one of our locations in Boston, Pittsburgh, or Las Vegas to support collaboration, or this role can be fully remote.

About the Role
Our Platform Infrastructure team is the backbone of everything we do at Attentive, providing a resilient and cost-effective platform that seamlessly handles billions of events from over 100 million customers daily. We own everything from compute, persistence, and networking to observability and deployments. Joining our team offers a high-growth career opportunity to collaborate with some of the world’s most talented engineers in a high-performance, high-impact culture.

What You’ll Accomplish

• Spearhead FinOps initiatives to increase cost transparency and optimize resource utilization across teams
• Provide guidance and mentorship to engineers on cost-optimization best practices
• Collaborate with teams across the organization to implement cost-saving measures
• Analyze, troubleshoot, coordinate, and resolve complex infrastructure issues
• Proactively lead infrastructure initiatives that have a company-wide impact
• Partner with engineering teams to influence cost-effective architectural and design choices
• Develop automation workflows to enhance team productivity and efficiency
• Foster a culture of continuous improvement by encouraging innovative thinking and challenging established norms

Your Expertise

• Bachelor's degree in Computer Science, Engineering, or related field; Master’s degree preferred
• 2+ years of experience in FinOps or cloud cost management
• 5+ years of experience in cloud infrastructure management, development or related roles
• Proficiency in some of the following technologies: AWS, Datadog, Kubernetes, Vantage, Terraform, Java
• Strong analytical and problem-solving skills with a keen attention to detail
• Excellent communication and leadership abilities
• Ability to work collaboratively in a cross-functional team environment

What We Use

• Our infrastructure runs primarily in Kubernetes hosted in AWS’s EKS
• Infrastructure tooling includes Istio, Datadog, Terraform, CloudFlare, and Helm
• Our backend is Java / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, AirFlow, Postgres, and Redis, hosted via AWS
• Our frontend is built with React and TypeScript, and uses best practices like GraphQL, Storybook, Radix UI, Vite, esbuild, and Playwright
• Our automation is driven by custom and open source machine learning models, lots of data and built with Python, Metaflow, HuggingFace 🤗, PyTorch, TensorFlow, and Pandas

You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work.

For US based applicants:

• The US base salary range for this full-time position is $180,000 - $240,000 annually + equity + benefits
• Our salary ranges are determined by role, level and location

#LI-MN1

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About the Role
We’re looking for a highly driven Senior Software Engineer to join our Streaming team, which powers the backbone of Attentive’s messaging and personalization platform. Our event streaming systems handle over 2 million messages per second and sit at the heart of how product and data engineering teams build real-time, customer-facing experiences.

What You’ll Accomplish

• Architect and evolve Attentive’s next-generation event streaming platform: Design high-throughput, low-latency solutions that power mission-critical messaging, personalization, and data integration use cases across Attentive’s ecosystem
• Enhance self-service for product engineering and data teams: Build and refine self-serve tools for event observability, debugging, load testing, and system configuration, empowering teams to experiment and ship quickly
• Simplify and modernize streaming architecture: Remove unnecessary abstraction layers, enable direct access for power users, and ensure the platform is flexible for both “paved path” and advanced use cases
• Solve complex distributed systems challenges: Improve event delivery reliability, cost efficiency, and system integration for real-time and batch workloads
• Champion best practices and technology selection: Stay ahead of industry advancements in event streaming, advocating for tools and approaches that balance innovation with long-term reliability
• Collaborate across engineering: Partner with product, data, and infrastructure teams to launch new customer-facing features, integrations, and scalable solutions built on streaming infrastructure

Your Expertise

• 5+ years experience architecting and supporting high-throughput, distributed systems at scale—especially those involving event streaming or messaging platforms
• Deep understanding of the internals of distributed streaming frameworks such as Kafka, Flink, Pulsar, and/or Spark
• Proficient in Java (Spring Boot) and familiar with modern development practices, including object-oriented design, data structures, and algorithms
• Able to debug issues across the stack—from message serialization and event schemas to network and JVM tuning—and communicate tradeoffs clearly
• Familiar with resource scheduling, data locality, and how infrastructure choices impact cost and system behavior
• Experience with observability and developer tooling for streaming (e.g., tracing, metrics, replay).Infrastructure-as-code expertise (Terraform, Helm), comfortable with Kubernetes (EKS) and cloud-native environments
• Track record of modernizing platforms: sunsetting legacy systems, moving to managed services, or implementing self-service capabilities
• Excited by new technologies, but pragmatic about introducing them—focused on solving real business problems

What We Use

• Our infrastructure runs primarily in Kubernetes hosted in AWS’s EKS
• Infrastructure tooling includes Istio, Datadog, Terraform, CloudFlare, and Helm
• Our backend is Java / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, AirFlow, Postgres, and Redis, hosted via AWS
• Our frontend is built with React and TypeScript, and uses best practices like GraphQL, Storybook, Radix UI, Vite, esbuild, and Playwright
• Our automation is driven by custom and open source machine learning models, lots of data and built with Python, Metaflow, HuggingFace 🤗, PyTorch, TensorFlow, and Pandas

You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work.

For US based applicants:

• The US base salary range for this full-time position is $150,000-$210,000 annually + equity + benefits
• Our salary ranges are determined by role, level and location

#LI-AB2

By applying for this position, your data will be processed as per Attentive's Privacy Policy.

About the Role

Our Engineering team creates innovative product experiences that power personalized marketing at massive scale. We develop cutting-edge applications and systems that process 100s of billions of messages and events per year, enabling marketers to connect effectively with hundreds of millions of consumers. Joining our team offers a high-growth career opportunity to work with some of the world’s most talented engineers in a high-performance and high-impact culture.

As a Senior Software Engineer in our Intelligent Messaging, you will pioneer the future of personalized 1:1 marketing by architecting robust, scalable backend systems powered by advanced AI and LLMs, including cutting-edge Generative AI and GPT technologies. Collaborating with top-tier engineers, data scientists, product managers, and designers, you’ll craft the foundation and reshape the platform of multi-channel messaging experimentation to support innovative, AI-driven applications that empower marketers to forge deep, meaningful connections with consumers at scale. Your impactful work will drive the delivery of billions of tailored messages, transforming consumer shopping experiences and fueling success for the world’s leading brands.

What You’ll Accomplish

• Develop and maintain scalable backend systems for our customer-facing products, ensuring high performance and reliability.
• Collaborate with cross-functional teams to build applications that support multi-channel communications for marketers.
• Implement and optimize systems that process and deliver billions of messages daily.
• Improve code quality through code reviews, testing, and advocating for best practices.
• Identify and address technical debt to ensure the long-term health of our codebase.
• Drive architectural design and technical decisions, and stay current with emerging technologies to enhance our products.

Your Expertise

• 5+ years of professional experience in software development focusing on backend systems.
• Proficiency in Java, Python, or Go, with a strong understanding of object-oriented programming.
• Experience building and maintaining scalable, high-performance applications.
• Proven ability to collaborate effectively with cross-functional teams.
• Solid understanding of software development best practices, including code reviews, writing tests, and continuous integration.

Nice to Haves

• Experience with service-oriented architecture and distributed systems.
• Familiarity with AWS services and cloud infrastructure.
• Knowledge of databases such as DynamoDB, Postgres, or Redis.
• Experience with messaging systems or streaming platforms (e.g., Kafka, Pulsar).
• Familiarity with frontend development with React and TypeScript.
• Experience with DevOps practices and tools such as Docker and Kubernetes.

What We Use

• Our infrastructure runs primarily in Kubernetes hosted in AWS’s EKS.
• Infrastructure tooling includes Istio, Datadog,Terraform, CloudFlare, and Helm.
• Our backend is Java / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, Kinesis, AirFlow, Postgres, Planetscale, and Redis, hosted via AWS.
• Our frontend is built with React and TypeScript, and uses best practices like GraphQL, Storybook, Radix UI, Vite, esbuild, and PlaywrightOur automation is driven by custom and open source machine learning models, lots of data and built with Python, Metaflow, HuggingFace 🤗, PyTorch, TensorFlow, and Pandas.

You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work.

For US based applicants:

• The US base salary range for this full-time position is $190,000 - $230,000 annually + equity + benefits
• Our salary ranges are determined by role, level and location

#LI-EZ1

By applying for this position, your data will be processed as per Attentive's Privacy Policy.

Reddit has a flexible first workforce. At Reddit we continue to grow our teams with the best talent. We're completely remote friendly and will continue to be after the pandemic.

Advertising is Reddit’s primary revenue driver and we have an ambitious goal to turn it into a massive business. Although several large digital ad platforms already exist, advertisers are being increasingly drawn to Reddit because of our passionate communities. We believe our community-centric platform has created the opportunity for Reddit to build a highly differentiated ads business.

About the Ads Data Science Team:

The Ads Data Science team at Reddit leverages data to maximize advertiser value on Reddit through robust data foundations, metrics, and strategic insights generated through experimentation and cutting-edge DS methods. 

We work on a wide range of challenging problems in the areas of ads targeting, relevance modeling, auction optimization, measurement, and user experience. We are a highly collaborative team of passionate data scientists and engineers who are constantly pushing the boundaries of what's possible with machine learning and statistical modeling.

About the Role:

We are looking for a highly motivated and experienced Data Scientist to join our growing Ads Data Science team. As a Data Scientist, you will play a key role in developing as well as applying cutting-edge DS models/methods to improve our understanding of the dynamics that drive the success of our advertising platform, and identify opportunities to accelerate that success. You will work closely with stakeholders across product, engineering, sales, marketing, and data to identify opportunities, define metrics, and build solutions that drive significant impact for Reddit.

Responsibilities:

• Analyze large-scale datasets to identify trends, patterns, and insights that can be used to improve the effectiveness of our advertising platform
• Develop ML models & DS methods to for improved anomaly detection, prediction, pattern recognition
• Communicate findings and recommendations to stakeholders across the organization
• Collaborate with product, engineering, sales, and marketing partners to define product and program requirements and translate them into data science solutions
• Stay up-to-date on the latest advancements in machine learning and data science

Qualifications:

• Advanced degree (Masters or Ph.D.) in a quantitative field such as: Statistics, Mathematics, Physics, Economics, or Operations Research
• For M.S. holders: 3+ years of industry experience in applied science or data science roles
• For Ph.D. holders: 2+ years of industry experience in applied science or data science roles
• Strong understanding of statistical modeling, machine learning algorithms, causal inference and experimental design
• Experience with large-scale data processing and analysis using tools such as Spark, Hadoop, or Hive; knowledge of BigQuery a plus
• Proficiency in Python or R and experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch
• Experience with SQL and relational databases
• Excellent communication and presentation skills
• Passion for Reddit and the online advertising industry

Bonus Points:

• Experience with online advertising and ad tech
• Experience with causal inference and A/B testing
• Contributions to open-source projects or publications in relevant conferences or journals

Benefits:

• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Comprehensive Medical Benefits & Health Care Spending Account
• Registered Retirement Savings Plan with matching contributions
• Income Replacement Programs
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave

#LI-Remote

[Location: remote-friendly or any office location - SF, LA, CHI, NY]

Reddit has a flexible first workforce. At Reddit we continue to grow our teams with the best talent. We're completely remote friendly and will continue to be after the pandemic.

Advertising is Reddit’s primary revenue driver and we have an ambitious goal to turn it into a massive business. Although several large digital ad platforms already exist, advertisers are being increasingly drawn to Reddit because of our passionate communities. We believe our community-centric platform has created the opportunity for Reddit to build a highly differentiated ads business.

About the Ads Data Science Team:

The Ads Data Science team at Reddit leverages data to maximize advertiser value on Reddit through robust data foundations, metrics, and strategic insights generated through experimentation and cutting-edge DS methods. 

We work on a wide range of challenging problems in the areas of ads targeting, relevance modeling, auction optimization, measurement, and user experience. We are a highly collaborative team of passionate data scientists and engineers who are constantly pushing the boundaries of what's possible with machine learning and statistical modeling.

About the Role:

We are looking for a highly motivated and experienced Data Scientist to join our growing Ads Data Science team. As a Data Scientist, you will play a key role in developing as well as applying cutting-edge DS models/methods to improve our understanding of the dynamics that drive the success of our advertising platform, and identify opportunities to accelerate that success. You will work closely with stakeholders across product, engineering, sales, marketing, and data to identify opportunities, define metrics, and build solutions that drive significant impact for Reddit.

Responsibilities:

• Analyze large-scale datasets to identify trends, patterns, and insights that can be used to improve the effectiveness of our advertising platform
• Develop ML models & DS methods to for improved anomaly detection, prediction, pattern recognition
• Communicate findings and recommendations to stakeholders across the organization
• Collaborate with product, engineering, sales, and marketing partners to define product and program requirements and translate them into data science solutions
• Stay up-to-date on the latest advancements in machine learning and data science

Qualifications:

• Advanced degree (Masters or Ph.D.) in a quantitative field such as: Statistics, Mathematics, Physics, Economics, or Operations Research
• For M.S. holders: 3+ years of industry experience in applied science or data science roles
• For Ph.D. holders: 2+ years of industry experience in applied science or data science roles
• Strong understanding of statistical modeling, machine learning algorithms, causal inference and experimental design
• Experience with large-scale data processing and analysis using tools such as Spark, Hadoop, or Hive; knowledge of BigQuery a plus
• Proficiency in Python or R and experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch
• Experience with SQL and relational databases
• Excellent communication and presentation skills
• Passion for Reddit and the online advertising industry

Bonus Points:

• Experience with online advertising and ad tech
• Experience with causal inference and A/B testing
• Contributions to open-source projects or publications in relevant conferences or journals

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave

#LI-Remote

Reddit has a flexible first workforce. At Reddit we continue to grow our teams with the best talent. We're completely remote friendly and will continue to be after the pandemic.

Advertising is Reddit’s primary revenue driver and we have an ambitious goal to turn it into a massive business. Although several large digital ad platforms already exist, advertisers are being increasingly drawn to Reddit because of our passionate communities. We believe our community-centric platform has created the opportunity for Reddit to build a highly differentiated ads business.

About the Ads Data Science Team:

The Ads Data Science team at Reddit leverages data to maximize advertiser value on Reddit through robust data foundations, metrics, and strategic insights generated through experimentation and cutting-edge DS methods. 

We work on a wide range of challenging problems in the areas of ads and platform measurement, campaign and creative management, advertiser growth and retention, monetization, and the intersection of brand and community engagement. We are a highly collaborative team of passionate data scientists and engineers who are constantly pushing the boundaries of what's possible with machine learning and statistical modeling.

About the Role:

We are looking for a highly motivated and experienced Senior Data Scientist to join our growing Ads Data Science team. As a Senior Data Scientist, you will play a key role in developing as well as applying cutting-edge DS models/methods to improve the adoption and performance of our advertising platform through data-driven insights. You will work closely with product managers, engineers, and other data scientists to identify opportunities, define metrics, and build solutions that drive significant impact for Reddit.

Responsibilities:

• Design, develop, and apply DS solutions to inform improvements in advertiser experience and Reddit's ad platform
• Analyze large-scale datasets to identify trends, patterns, and insights that can be used to improve the effectiveness of our advertising platform
• Collaborate with product managers and engineers to define product requirements and translate them into data science solutions
• Develop ML models & DS methods to improve anomaly detection, prediction, & pattern recognition 
• Communicate findings and recommendations to stakeholders across the organization
• Stay up-to-date on the latest advancements in machine learning and data science
• Mentor and guide junior data scientists on the team

Qualifications:

• Advanced degree (Masters or Ph.D.) in a quantitative field such as: Statistics, Mathematics, Physics, Economics, or Operations Research
• For M.S. holders: 5+ years of industry experience in applied science or data science roles
• For Ph.D. holders: 4+ years of industry experience in applied science or data science roles
• Platform experience and a deep understanding of the ads ecosystem
• Strong understanding of statistical modeling, machine learning algorithms, causal inference and experimental design
• Experience with large-scale data processing and analysis using tools such as Spark, Hadoop, or Hive; knowledge of BigQuery a plus
• Proficiency in Python or R and experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch
• Experience with SQL and relational databases
• Excellent communication and presentation skills
• Passion for Reddit and the online advertising industry

Bonus Points:

• Experience with online advertising and ad tech
• Experience with causal inference and A/B testing
• Contributions to open-source projects or publications in relevant conferences or journals

Benefits:

• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Comprehensive Medical Benefits & Health Care Spending Account
• Registered Retirement Savings Plan with matching contributions
• Income Replacement Programs
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave

#LI-Remote

Location: US remote-friendly

Reddit has a flexible first workforce. At Reddit we continue to grow our teams with the best talent. We're completely remote friendly and will continue to be after the pandemic.

Advertising is Reddit’s primary revenue driver and we have an ambitious goal to turn it into a massive business. Although several large digital ad platforms already exist, advertisers are being increasingly drawn to Reddit because of our passionate communities. We believe our community-centric platform has created the opportunity for Reddit to build a highly differentiated ads business.

About the Ads Data Science Team:

The Ads Data Science team at Reddit leverages data to maximize advertiser value on Reddit through robust data foundations, metrics, and strategic insights generated through experimentation and cutting-edge DS methods. 

We work on a wide range of challenging problems in the areas of ads and platform measurement, campaign and creative management, advertiser growth and retention, monetization, and the intersection of brand and community engagement. We are a highly collaborative team of passionate data scientists and engineers who are constantly pushing the boundaries of what's possible with machine learning and statistical modeling.

About the Role:

We are looking for a highly motivated and experienced Senior Data Scientist to join our growing Ads Data Science team. As a Senior Data Scientist, you will play a key role in developing as well as applying cutting-edge DS models/methods to improve the adoption and performance of our advertising platform through data-driven insights. You will work closely with product managers, engineers, and other data scientists to identify opportunities, define metrics, and build solutions that drive significant impact for Reddit.

Responsibilities:

• Design, develop, and apply DS solutions to inform improvements in advertiser experience and Reddit's ad platform
• Analyze large-scale datasets to identify trends, patterns, and insights that can be used to improve the effectiveness of our advertising platform
• Collaborate with product managers and engineers to define product requirements and translate them into data science solutions
• Develop ML models & DS methods to improve anomaly detection, prediction, & pattern recognition 
• Communicate findings and recommendations to stakeholders across the organization
• Stay up-to-date on the latest advancements in machine learning and data science
• Mentor and guide junior data scientists on the team

Qualifications:

• Advanced degree (Masters or Ph.D.) in a quantitative field such as: Statistics, Mathematics, Physics, Economics, or Operations Research
• For M.S. holders: 5+ years of industry experience in applied science or data science roles
• For Ph.D. holders: 4+ years of industry experience in applied science or data science roles
• Platform experience and a deep understanding of the ads ecosystem
• Strong understanding of statistical modeling, machine learning algorithms, causal inference and experimental design
• Experience with large-scale data processing and analysis using tools such as Spark, Hadoop, or Hive; knowledge of BigQuery a plus
• Proficiency in Python or R and experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch
• Experience with SQL and relational databases
• Excellent communication and presentation skills
• Passion for Reddit and the online advertising industry

Bonus Points:

• Experience with online advertising and ad tech
• Experience with causal inference and A/B testing
• Contributions to open-source projects or publications in relevant conferences or journals

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave  

#LI-Remote

About the Role
The Onsite Customer Growth team builds the features that help Attentive’s customers grow directly on their websites. Our mission is to accelerate list growth and improve conversion by delivering creative, high performing onsite experiences powered by strong engineering and intelligent AI driven optimization.

What You’ll Accomplish

• Lead, mentor, and grow a high performing engineering team responsible for building the backend systems powering onsite customer growth products
• Set the technical vision and roadmap for backend services, APIs, and data driven systems that power personalized onsite experiences at scale
• Partner closely with AI, data, and product teams to develop intelligent capabilities that improve performance and user experience
• Ensure the reliability, scalability, and performance of the systems that support customer growth and real time user interactions
• Drive best practices in design discussions, code reviews, architecture decision making, and operational excellence
• Foster a learning oriented team culture that encourages collaboration, curiosity, ownership, and continuous improvement
• Own delivery of key product initiatives, balancing long term platform investments with near term business objectives
• Promote clean, maintainable, well tested code and high engineering standards across the team

Your Expertise

• 7+ years of professional backend software engineering experience, including at least two years managing or leading engineers
• Strong proficiency in one or more modern programming languages such as Java, or Typescript
• Experience designing and operating distributed systems, APIs, and microservice architectures at scale
• Hands on familiarity with cloud platforms such as AWS and containerization technologies such as Docker or Kubernetes
• Deep understanding of databases, messaging systems, or streaming technologies such as PostgreSQL, Redis, or Kafka
• Track record of building reliable, scalable, high throughput systems that support customer facing products
• Demonstrated ability to coach and develop engineers, drive team alignment, and create an inclusive, collaborative engineering environment
• Strong communication and cross functional partnership skills, with the ability to work effectively with AI, data, product, and design teams
• A mindset rooted in ownership, curiosity, and a passion for building meaningful systems that drive measurable customer impact

What We Use

• Our infrastructure runs primarily in Kubernetes hosted in AWS’s EKS
• Infrastructure tooling includes Istio, Datadog, Terraform, CloudFlare, and Helm
• Our backend is Java / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, AirFlow, Postgres, and Redis, hosted via AWS
• Our frontend is built with React and TypeScript, and uses best practices like GraphQL, Storybook, Radix UI, Vite, esbuild, and Playwright
• Our automation is driven by custom and open source machine learning models, lots of data and built with Python, Metaflow, HuggingFace 🤗, PyTorch, TensorFlow, and Pandas

You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work.

For US based applicants:

• The US base salary range for this full-time position is $193,000 - $250,000 annually + equity + benefits
• Our salary ranges are determined by role, level and location

#LI-MN1

By applying for this position, your data will be processed as per Attentive's Privacy Policy.

As a Senior Software Engineer, you will be tasked with leading the architectural design and technical strategy for high-performance systems that process massive volumes of telemetry data while reducing costs and improving insights for enterprise customers. You will drive technical excellence and lead complex engineering initiatives at scale for the Observo.ai team, our cutting-edge AI-driven data pipeline optimization platform.

What Will You Do?

Primary responsibilities include:

• Lead the architectural design and technical roadmap for scalable, high-performance data processing pipelines capable of handling petabyte-scale telemetry data (logs, metrics, traces).
• Drive the development and optimization of ML-driven data routing and transformation engines to reduce customer data volumes by 80%+ while architecting real-time analytics systems using advanced machine learning and LLMs.
• Design cloud-native microservices and APIs that integrate seamlessly with major observability platforms (Splunk, Elastic, Datadog) while establishing robust monitoring, alerting, and observability solutions.
• Lead cross-functional technical initiatives and decision-making forums, collaborating with Product, Data Science, and DevOps teams to translate strategic vision into technical solutions and company-wide standards.
• Provide technical leadership and mentorship to senior and junior engineers, driving system performance and reliability optimization while establishing engineering best practices and culture.

What Skills and Knowledge Will You Bring?

Ideal candidates will have:

• 5+ years of software engineering experience focused on distributed systems, data engineering, or ML infrastructure with expert-level proficiency in Go, Rust, or Java.
• Extensive experience with cloud platforms (AWS, GCP, Azure), container orchestration (Kubernetes), and a proven track record leading and scaling data pipelines using Kafka, Spark, or Flink.
• Deep expertise in database technologies (SQL and NoSQL) and advanced experience with machine learning frameworks (TensorFlow, PyTorch) and MLOps practices for production ML systems.
• Expert knowledge of observability tools and standards, including Prometheus, Grafana, ELK stack, OpenTelemetry, and Parquet, alongside extensive experience with Infrastructure as Code (Terraform).
• Strong leadership and technical communication skills, with a track record of mentoring engineers, planning technical strategy, and driving decisions across multiple teams and stakeholders.

Why SentinelOne?

AI is redefining how the world operates and rewriting the rules of security in real time, and SentinelOne was built for this moment. From day one, we architected an AI-native platform designed to operate at machine speed, not as an add-on to legacy systems but as the foundation itself. If you want to build where innovation and impact move together, this is that place.

We invest in our Sentinels with comprehensive, competitive benefits designed to support you and your family:

• Medical, Vision, Dental, 401(k), Commuter, Health and Dependent FSA
• Unlimited PTO
• Industry-leading gender-neutral parental leave
• Paid company holidays
• Paid sick time
• Employee stock purchase program
• Disability and life insurance
• Employee assistance program
• Gym membership reimbursement
• Cell phone reimbursement
• Numerous company-sponsored events, including regular happy hours and team-building events

As a Principal Machine Learning Engineer within the Creator Services Machine Intelligence team, you will focus on the research and development of Embodied AI and Behavioral Agents that revolutionize how games are created and played on Roblox. You will bridge the gap between cutting-edge research and massive-scale product application, building agents capable of complex 3D gameplay and unblocking many use cases across Roblox, from automated playtesting to ensure quality, to "Smart NPCs" with human-like movement and strategic reasoning, playing with real players in games.

You will work on Imitation Learning (IL), Reinforcement Learning (RL), Computer Vision, Computer Graphics, Robotics, and Agentic Reasoning to create generalizable agents that can perceive 3D environments, understand game rules, plan long-term strategies, and execute complex physics-based actions.

You Will:

• Report to the Engineering Manager of Creator Services Machine Intelligence.
• Design and implement foundation models for embodied agents that master both fluid, human-like movement and high-level strategic reasoning.
• Define the long-term roadmap for Game AI and Embodied Intelligence, acting as a technical bar-raiser for code quality and architectural design.
• Balance the exploration of cutting-edge deep learning research with the practical constraints of serving models to millions of concurrent users.
• Mentor fellow engineers and researchers, fostering a culture of technical excellence and scientific inquiry.
• Collaborate with Product Managers, Backend and Game Engine Engineers and other Roblox team members.

You Have:

• PhD or Master’s in Computer Science, Applied Math, or other field. A record of top-tier publications (e.g., NeurIPS, ICML, CVPR, AAAI, SIGGRAPH, etc) in embodied agents or related domains is a plus.
• 7+ years of experience as a Machine Learning Engineer or Research Scientist, applying research to tangible products.
• Deep technical understanding of Imitation Learning, Robotics, Reinforcement Learning, Computer Graphics and Vision, with experience working on low-latency motor control (human-like movement) and high-level strategic reasoning (game rules/goals).
• Proficiency in Python (PyTorch/TensorFlow) and familiarity with C#, C++, or similar systems languages.
• Experience training models on large-scale distributed clusters and understanding the challenges of inference in real-time gaming environments.
• A passion for bridging the gap between research and production, moving beyond academic benchmarks to launch scalable solutions that directly impact millions of users.

As a Senior Machine Learning Engineer, you will work on challenging problems leveraging state-of-art AI/ML to empower a new generation of Roblox experiences for our growing community of users. We are looking for senior AI/ML engineers to lead the vision of low compute cost, in experience machine learning at Roblox, taking leads on designing core components of on-device ML operations. We are designing a system for advancing model architecture, enabling more efficient deployment to cloud and client, while delivering on complex operations including Generative AI model deployment. The engineer will be driving the architecture optimization across a large range of compute devices, making efficient use of available compute resources. Join us in our exciting journey!

You will:

• Develop and implement state-of-the-art ML models
• Stay up-to-date with the latest research in ML and related fields, and apply this knowledge to improve the model performance
• Establish a pipeline for delivering Roblox ML model on range of computing devices
• Build cross-functional partnership on deployment and architecture optimization
• Design and implement primary components of the in-experience machine learning system.

You have:

• • 2+ years experience in developing machine learning models, preferably in image, video, audio or 3D representations with Python
  • A strong understanding of deep learning frameworks including PyTorch and Tensorflow.
  • Experience in shipping ML features in production environments, including low powered devices.
  • Excellent cross-functional skills, partnering with organization leaders, driving to a conclusion.
  • Knowledge in state-of-the-art deep learning network architectures and primitives.
  • Experience with model optimization techniques.

At Roblox, computer vision and graphics power the way our global community discovers, creates, and interacts on our virtual platform. This role involves building cutting-edge models to interpret and analyze every form of content—experiences, text, images, videos, and 3D avatars. Your work will directly influence core systems that drive the next generation of creation, search, recommendations, and trust & safety initiatives across our massive ecosystem.

We’re looking for PhD candidates passionate about the intersection of computer vision, graphics, and generative modeling. You’ll work on applied research and engineering projects with direct production impact — enabling new ways for creators and players to bring ideas to life.

Teams Hiring for This Role

• Content Understanding: Develop large-scale computer vision and multimodal models that classify, organize, and recommend 3D and visual content to improve user discovery, personalization, and safety.
• Account Identity: Focuses on various aspects of user identity from bot detection, alternate account detection graph, to age estimation based on behavioral and facial features.
• Safety AI Systems: Develop AI that automatically inspects and filters the vast array of user-generated content on Roblox – from images and videos to audio files, 3D meshes, and entire games. This includes CV models to detect unsafe images, audio analysis to screen sound and music, and novel techniques for 3D content and code moderation.

You Will:

• Design and implement foundation models for visual and 3D-based creation, search, and recommendations, ensuring a high level of fidelity, relevance, and ranking.
• Break down complex product requirements into iterative deliverable stages, moving applied research into high-scale production systems.
• Implement innovative visual and multi-modal models that power core Roblox functions (e.g., world creation, avatar systems, search, and recommendations).
• Build high precision facial age estimation across demographics from ground up including various fraud detection techniques for a robust and safe user identity system. 

You Have

• Possessing or pursuing a PhD in computer science, engineering, or a related field, with a thesis aligned to Roblox’s research areas.
• Expertise in one or more areas: computer vision, multimodal learning, 3D Graphics, or large-scale representation learning.
• Experience developing and training deep learning models using modern frameworks (PyTorch, TensorFlow, JAX).
• A strong research track record, evidenced by multiple publications and presentations in top-tier, peer-reviewed venues.
• Proficiency in one or more programming languages (e.g., Python, C++, Go, Java) and experience building and optimizing large-scale systems.

Apply now to be considered for anticipated positions.

You may redact age, date of birth, and dates of attendance/graduation from your resume if you prefer.

As you apply, you can find more information about our process by signing up for Speak_. You'll gain access to our practice assessment, comprehensive guides, FAQs, and modules designed to help you ace the hiring process.

Expression of Interest

We know that for the most talented engineers, the right opportunity is about more than just a job title, it’s about the right challenge at the right time. Even if our current openings don't perfectly fit your timing and interests today, we still want to hear from you. We view this as a priority pathway to connect with curious, driven MLEs whose unique expertise can help us architect the next generation of planet-scale ML systems. 

At Moloco, our mission is to empower the global digital economy by turning massive first-party data into measurable business outcomes. Whether it’s optimizing real-time bidding for Moloco Ads or building AI-native stacks for Streaming and Commerce, we’re looking for engineers to help us lead the shift toward a more performance-driven, AI-powered internet.

If you’re excited to scale and innovate in a fast-moving environment, share your profile and we will reach out the moment we see a potential match for your experiences and future goals.

About the Role

As a Machine Learning Engineer at Moloco, you will design, train, and deploy the large‑scale models that power our programmatic advertising and commerce media products. You will work at the heart of our real-time bidding and pricing systems, helping shape an end-to-end ML ecosystem that processes billions of daily events. Your work will directly improve marketplace performance for global advertisers and publishers by optimizing for relevance, ROI, and user experience at a scale few companies can match.

The Opportunity

• Architect and iterate on high-performance models that improve ad relevance, click-through rates, and conversion performance.
• Productionize and maintain scalable ML pipelines - from data ingestion to online inference - on top of planet-scale infrastructure.
• Extract insights from massive datasets of user behavior and auction signals to define new features and refine modeling strategies.
• Translate business goals (revenue, ROI, engagement) into concrete modeling challenges and success metrics in collaboration with Product and Data Science.
• Validate innovation through rigorous experimentation, including A/B tests, offline evaluations, and counterfactual analyses.
• Balance marketplace health by implementing models that harmonize advertiser value with a high-quality user experience.
• Enhance system reliability by refining feature stores, monitoring data quality, and establishing robust debugging practices.
• Drive platform evolution, contributing to ML tools and guidelines that increase experimentation velocity and deployment speed.
• Optimize for performance, partnering with Infra teams to reduce latency and improve throughput for low-cost, high-scale decisioning.
• Elevate technical excellence by sharing best practices in modeling and production ML with the broader engineering team.

Expertise We Value:

MLEs at Moloco are hands-on builders of some of the world’s highest-scale ML workloads. They bridge technical innovation with global revenue outcomes, owning the critical systems that define our next generation of machine learning and optimization platforms.

While every journey is unique, we find that the most successful MLEs at Moloco bring a deep technical foundation in the following areas:

• Production ML at Scale: 5-12+ years of experience delivering ML solutions in high-stakes production environments (e.g., Ads, Recommenders, Search, or Marketplaces), with a track record of scaling models for massive throughput and low-latency requirements.
• Algorithmic Mastery: A strong foundation in ML and statistics applied to real-world business challenges, with expertise in areas such as ranking, calibration, exploration-exploitation, causal inference, or multi‑objective optimization.
• Full-Lifecycle Engineering: Deep understanding of the end-to-end ML lifecycle, including data pipelining, feature engineering, model architecture, inference optimization, and the deployment of models into online systems.
• Technical Versatility: Proficiency across a modern ML toolkit (Python, SQL, and frameworks like TensorFlow or PyTorch) and experience leveraging data processing stacks like Spark, Beam, or Flink to deliver results at scale.
• Operational Stewardship: Experience ensuring the long-term health of ML systems in live environments—monitoring performance, diagnosing drift, and iterating based on real-world feedback to maintain measurable impact.
• Technical Mentorship: A passion for advancing the team’s collective bar by sharing best practices for large-scale ML systems and guiding the technical direction of complex machine learning initiatives.

Our Tech Stack:

• Languages: Python, Go, C++
• ML Frameworks: TensorFlow, PyTorch, JAX
• Infrastructure: GCP, AWS, Kubernetes, Spark, BigQuery, BigTable

How You Work: 

• Your ethos is ownership
• You thrive in ambiguity and enjoy partnering with others to shape vague requirements into clear roadmaps with pragmatic tradeoffs.
• You take shared accountability for the end-to-end journey; communicating progress, surfacing risks early, and following through to ensure your work creates measurable value.
• You demonstrate strong judgment under uncertainty. 
• You prioritize based on long-term impact, over short-term noise, making deliberate decisions when information is incomplete.
• You explicitly weigh tradeoffs like speed vs. quality and remain agile enough to adjust your approach thoughtfully as new information/data emerges.
• You lead through clarity and active listening. 
• You reduce ambiguity for the team by asking the right questions upfront, tailor your communication to your audience, document your decisions, and bring helpful structure to complex discussions. 
• You provide thoughtful, evidence-based feedback when needed and align behind decisions once they are made.
• You collaborate early, instead of solving in isolation.
• You build trust across the organization by listening first and navigate conflicting needs with empathy, creating buy-in around priorities and scope. 
• You navigate technical tensions productively, disagreeing thoughtfully while maintaining momentum and strengthening professional relationships.
• You fall in love with the problem, not the solution
• You build for the long run, looking beyond immediate tasks to understand root causes, second-order effects, and the long-term health of our ML ecosystem. 
• When something breaks, you don’t just patch it; you seek structural improvements that prevent recurrence and elevate the technical bar for the entire organization.
• You prioritize customer impact and take action to make it real.
• You prioritize effective solutions that drive business impact over technical elegance, spotting opportunities that others might overlook. 
• You have the initiative to turn ideas into outcomes and the agency to identify and fix gaps, even when they aren’t yet on the formal roadmap.

You can apply for this role through our Open Positions page (or through our Internal Job Board if you are a current employee). We will review submissions on an ongoing basis.

The Impact You’ll Be Contributing to Moloco:

As a Senior Machine Learning Engineer on Moloco’s Ads Quality team, you’ll design and scale machine learning systems that directly improve ad relevance, ranking, and optimization. Your work will have a measurable impact on advertiser performance, revenue efficiency, and the overall user experience across Moloco’s ad platform.

The Opportunity:

• Design, build, and deploy large-scale ML systems for ad ranking, click-through prediction, and conversion optimization
• Develop and operate production pipelines that process hundreds of millions of ad requests per day with low-latency requirements
• Collaborate directly with customers and partners in Mandarin to understand business goals and deliver data-driven ML solutions
• Apply systematic, reproducible approaches to model training, evaluation, and continuous improvement
• Partner with the Machine Learning Infrastructure and Data teams to improve tooling, deployment pipelines, and training efficiency
• Lead design and code reviews to promote technical excellence and standardize ML practices across Ads teams
• Diagnose model performance, identify optimization opportunities, and execute experiments that drive measurable results
• Mentor engineers on best practices for ML experimentation, productionization, and scaling
• Work cross-functionally with product, infrastructure, and business teams to align technical innovations with product goals

How Do I Know if the Role is Right For Me?

• You have 7+ years of experience building and deploying ML systems at scale, ideally in AdTech, recommender systems, or search/ranking domains
• You’ve shipped models that directly improved key product or business metrics such as CTR, CVR, or ROI
• You’re fluent in Mandarin Chinese and skilled at collaborating with customers or partners in technical discussions
• You have strong software engineering fundamentals: data structures, algorithms, and system design and proficiency in Python (C++ or Java a plus)
• You’re experienced with modern ML frameworks such as PyTorch, TensorFlow, or JAX
• You’ve worked with distributed data and compute systems like Apache Beam, Dataflow, or Flume
• You understand how to build robust ML pipelines including data versioning, feature engineering, retraining, and model monitoring in production
• You have experience optimizing inference performance on GPUs, TPUs, or similar hardware accelerators
• You thrive in fast-moving, ambiguous environments and can translate complex technical work into measurable business outcomes
• You value collaboration, accountability, and building systems that scale across teams and markets

What You’ll Do:

As a strong AI and ML fundamentalist who is an expert at developing cutting-edge AI solutions to complex problems, you will develop code that eventually integrates into production and be responsible for:

• Design, implement, and evaluate novel machine learning and deep learning algorithms.
• Iterate on AI model development; starting from the data needed for training, architecture, input/output representations, evaluation, and deployment. 
• Collaborate with other researcher engineers to prototype and validate complex solutions from academic literature.
• Conduct experiments to benchmark new techniques and evaluate model behavior.
• Develop tools and frameworks to support scalable and reproducible research and development.
• Communicate research findings to leadership in a concise, and convincing manner.
• Stay current with the latest developments in AI/ML and identify relevant innovations.
• Assist in transitioning research prototypes into production-ready systems.

What You Need:

• M.S or PhD degree in Computer Science, or Computer Engineering with strong emphasis on AI and ML.
• Enjoys solving less-defined and complex problems
• Familiarity with good SW practices and development, including code quality, version control, etc.
• Very strong with ML frameworks such as Pytorch, or Tensorflow
• Good understanding of Transformer architectures, attention mechanisms, multi-modal foundation models, diffusion policies, fine-tuning, model distillation, mixture of experts, and other similar topics.
• Has strong ability to debug and determine requirements for AI models in terms of data, training, and evaluation.
• Is up to date with research literature and recent ML techniques and methodologies.

Bonus Qualifications:

• Experience with Reinforcement Learning, self-supervised training, and imitation learning is a plus.
• Experience developing VLA (Vision Language Action) models for robotic manipulation and mobility is a plus.
• Experience developing production AI models is a plus.
• Publications at top conferences are a plus.

Please note that this job description is intended to provide a general overview of the position and does not include an exhaustive list of responsibilities and qualifications

At Archer we aim to attract, retain, and motivate talent that possess the skills and leadership necessary to grow our business. We drive a pay-for-performance culture and reward performance that supports the Company’s business strategy. For this position we are targeting a base pay between $160,000.00 - $180,000.00 Actual compensation offered will be determined by factors such as job-related knowledge, skills, and experience.

Archer is proud to be an Equal Opportunity employer committed to diversity and inclusivity in the workplace. All aspects of employment are decided on the basis of merit, qualifications, and business needs. We do not discriminate based upon race, color, religion, sex, sexual orientation, age, national origin, disability status, protected veteran status, gender identity or any other characteristic protected by federal, state or local laws.

Archer is committed to working with and providing reasonable accommodations to job applicants with physical or mental disabilities, and those with sincerely held religious beliefs. Applicants who may require reasonable accommodation for any part of the application or hiring process should provide their name and contact information to Archer’s People Team at people@archer.com. Reasonable accommodations will be determined on a case-by-case basis.

What You’ll Do:

As a Staff AI and ML fundamentalist who is an expert at developing cutting-edge AI solutions to complex problems, you will develop code that eventually integrates into production and be responsible for:

• Design, implement, and evaluate novel machine learning and deep learning algorithms.
• Iterate on AI model development; starting from the data needed for training, architecture, input/output representations, evaluation, and deployment. 
• Collaborate with other researcher engineers to prototype and validate complex solutions from academic literature.
• Conduct experiments to benchmark new techniques and evaluate model behavior.
• Develop tools and frameworks to support scalable and reproducible research and development.
• Communicate research findings to leadership in a concise, and convincing manner.
• Stay current with the latest developments in AI/ML and identify relevant innovations.
• Assist in transitioning research prototypes into production-ready systems.

What You Need:

• M.S or PhD degree in Computer Science, or Computer Engineering with strong emphasis on AI and ML.
• Enjoys solving less-defined and complex problems
• Familiarity with good SW practices and development, including code quality, version control, etc.
• Very strong with ML frameworks such as Pytorch, or Tensorflow
• Good understanding of Transformer architectures, attention mechanisms, multi-modal foundation models, diffusion policies, fine-tuning, model distillation, mixture of experts, and other similar topics.
• Has strong ability to debug and determine requirements for AI models in terms of data, training, and evaluation.
• Is up to date with research literature and recent ML techniques and methodologies.

Bonus Qualifications:

• Experience with Reinforcement Learning, self-supervised training, and imitation learning is a plus.
• Experience developing VLA (Vision Language Action) models for robotic manipulation and mobility is a plus.
• Experience developing production AI models is a plus.
• Publications at top conferences are a plus.

Please note that this job description is intended to provide a general overview of the position and does not include an exhaustive list of responsibilities and qualifications

At Archer we aim to attract, retain, and motivate talent that possess the skills and leadership necessary to grow our business. We drive a pay-for-performance culture and reward performance that supports the Company’s business strategy. For this position we are targeting a base pay between $190,000 - $240,000 Actual compensation offered will be determined by factors such as job-related knowledge, skills, and experience.

Archer is proud to be an Equal Opportunity employer committed to diversity and inclusivity in the workplace. All aspects of employment are decided on the basis of merit, qualifications, and business needs. We do not discriminate based upon race, color, religion, sex, sexual orientation, age, national origin, disability status, protected veteran status, gender identity or any other characteristic protected by federal, state or local laws.

Archer is committed to working with and providing reasonable accommodations to job applicants with physical or mental disabilities, and those with sincerely held religious beliefs. Applicants who may require reasonable accommodation for any part of the application or hiring process should provide their name and contact information to Archer’s People Team at people@archer.com. Reasonable accommodations will be determined on a case-by-case basis.

What You’ll Do:

As a Principal AI and ML fundamentalist who is an expert at developing cutting-edge AI solutions to complex problems, you will develop code that eventually integrates into production and be responsible for:

• Design, implement, and evaluate novel machine learning and deep learning algorithms.
• Iterate on AI model development; starting from the data needed for training, architecture, input/output representations, evaluation, and deployment. 
• Collaborate with other researcher engineers to prototype and validate complex solutions from academic literature.
• Conduct experiments to benchmark new techniques and evaluate model behavior.
• Develop tools and frameworks to support scalable and reproducible research and development.
• Communicate research findings to leadership in a concise, and convincing manner.
• Stay current with the latest developments in AI/ML and identify relevant innovations.
• Assist in transitioning research prototypes into production-ready systems.

What You Need:

• M.S or PhD degree in Computer Science, or Computer Engineering with strong emphasis on AI and ML.
• Enjoys solving less-defined and complex problems
• Familiarity with good SW practices and development, including code quality, version control, etc.
• Very strong with ML frameworks such as Pytorch, or Tensorflow
• Good understanding of Transformer architectures, attention mechanisms, multi-modal foundation models, diffusion policies, fine-tuning, model distillation, mixture of experts, and other similar topics.
• Has strong ability to debug and determine requirements for AI models in terms of data, training, and evaluation.
• Is up to date with research literature and recent ML techniques and methodologies.

Bonus Qualifications:

• Experience with Reinforcement Learning, self-supervised training, and imitation learning is a plus.
• Experience developing VLA (Vision Language Action) models for robotic manipulation and mobility is a plus.
• Experience developing production AI models is a plus.
• Publications at top conferences are a plus.

Please note that this job description is intended to provide a general overview of the position and does not include an exhaustive list of responsibilities and qualifications

At Archer we aim to attract, retain, and motivate talent that possess the skills and leadership necessary to grow our business. We drive a pay-for-performance culture and reward performance that supports the Company’s business strategy. For this position we are targeting a base pay between $270,000.00 - $340,000.00 Actual compensation offered will be determined by factors such as job-related knowledge, skills, and experience.

Archer is proud to be an Equal Opportunity employer committed to diversity and inclusivity in the workplace. All aspects of employment are decided on the basis of merit, qualifications, and business needs. We do not discriminate based upon race, color, religion, sex, sexual orientation, age, national origin, disability status, protected veteran status, gender identity or any other characteristic protected by federal, state or local laws.

Archer is committed to working with and providing reasonable accommodations to job applicants with physical or mental disabilities, and those with sincerely held religious beliefs. Applicants who may require reasonable accommodation for any part of the application or hiring process should provide their name and contact information to Archer’s People Team at people@archer.com. Reasonable accommodations will be determined on a case-by-case basis.

What You’ll Do:

As a strong AI and ML fundamentalist who is an expert at developing cutting-edge AI solutions to complex problems, you will develop code that eventually integrates into production and be responsible for:

• Design, implement, and evaluate novel machine learning and deep learning algorithms.
• Iterate on AI model development; starting from the data needed for training, architecture, input/output representations, evaluation, and deployment. 
• Collaborate with other researcher engineers to prototype and validate complex solutions from academic literature.
• Conduct experiments to benchmark new techniques and evaluate model behavior.
• Develop tools and frameworks to support scalable and reproducible research and development.
• Communicate research findings to leadership in a concise, and convincing manner.
• Stay current with the latest developments in AI/ML and identify relevant innovations.
• Assist in transitioning research prototypes into production-ready systems.

What You Need:

• M.S or PhD degree in Computer Science, or Computer Engineering with strong emphasis on AI and ML.
• Enjoys solving less-defined and complex problems
• Familiarity with good SW practices and development, including code quality, version control, etc.
• Very strong with ML frameworks such as Pytorch, or Tensorflow
• Good understanding of Transformer architectures, attention mechanisms, multi-modal foundation models, diffusion policies, fine-tuning, model distillation, mixture of experts, and other similar topics.
• Has strong ability to debug and determine requirements for AI models in terms of data, training, and evaluation.
• Is up to date with research literature and recent ML techniques and methodologies.

Bonus Qualifications:

• Experience with Reinforcement Learning, self-supervised training, and imitation learning is a plus.
• Experience developing VLA (Vision Language Action) models for robotic manipulation and mobility is a plus.
• Experience developing production AI models is a plus.
• Publications at top conferences are a plus.

Please note that this job description is intended to provide a general overview of the position and does not include an exhaustive list of responsibilities and qualifications

At Archer we aim to attract, retain, and motivate talent that possess the skills and leadership necessary to grow our business. We drive a pay-for-performance culture and reward performance that supports the Company’s business strategy. For this position we are targeting a base pay between $160,000.00 - $180,000.00 Actual compensation offered will be determined by factors such as job-related knowledge, skills, and experience.

Archer is proud to be an Equal Opportunity employer committed to diversity and inclusivity in the workplace. All aspects of employment are decided on the basis of merit, qualifications, and business needs. We do not discriminate based upon race, color, religion, sex, sexual orientation, age, national origin, disability status, protected veteran status, gender identity or any other characteristic protected by federal, state or local laws.

Archer is committed to working with and providing reasonable accommodations to job applicants with physical or mental disabilities, and those with sincerely held religious beliefs. Applicants who may require reasonable accommodation for any part of the application or hiring process should provide their name and contact information to Archer’s People Team at people@archer.com. Reasonable accommodations will be determined on a case-by-case basis.

The Team

The Machine Learning Platform team builds the foundational technology that scales machine learning innovation across Upstart. As a Principal Machine Learning Engineer, you will work at the intersection of applied ML and platform engineering—collaborating closely with Research Scientists, Data Scientists, and ML Platform Engineers to design tools and systems that accelerate model development to ultimately improve predictive accuracy. Success in this role requires deep knowledge of ML throughout the entire modeling lifecycle - from data preparation to training and deployment to production.

In this role, you will lead engineering initiatives that turn high-impact modeling needs into scalable, reusable infrastructure. This includes building a unified embeddings platform for training, serving, and managing representations at scale; streamlining feature engineering pipelines to reduce manual steps and deliver new signals quickly; developing automated continuous-learning systems that handle data refresh, retraining, evaluation, and drift monitoring with minimal manual effort; and scaling our training pipelines to support larger datasets, more complex architectures, and faster experimentation.

Across all of these efforts, you will work backward from applied ML projects that meaningfully improve accuracy—using those real-world scenarios to harden the platform capabilities that enable ML teams across Upstart to innovate with greater speed, reliability, and impact.

How You’ll Make an Impact

• Scale ML innovation by building tools, infrastructure, and workflows that dramatically improve the speed and reliability of model development.
• Work backward from modeling needs to design systems that directly unlock gains in accuracy, efficiency, and scientific productivity.
• Explore new algorithms and methodologies for our machine learning models and develop tooling to support them
• Improve the entire ML lifecycle—from data readiness and feature development through training, evaluation, serving, and monitoring.
• Automate and standardize operational workflows, enabling scientists to focus on high-leverage modeling and analysis rather than manual pipelines.
• Define the roadmap for our next generation ML Platform, balancing near-term impact with long-term architectural scalability.
• Collaborate cross-functionally with Data Engineering, ML Platform, Pricing, and other teams to build reliable, end-to-end ML systems.

Your work will multiply the effectiveness of every ML team at Upstart—accelerating innovation and advancing our mission to make credit more accurate, accessible, and fair.

This is a high influence role suited for those who enjoy combining science innovation, with cross functional collaboration and advisory. 

Minimum Qualifications

• 7+ years of hands-on experience in applied machine learning, with strong exposure to production-scale modeling efforts.
• Demonstrated expertise in end-to-end model development: data prep, feature engineering, training, evaluation, and deployment.
• Experience working in high-scale, ML-driven product environments—especially in fintech, pricing, or risk modeling.
• Proficiency in Python and core ML frameworks (e.g., PyTorch, TensorFlow, Scikit-learn, XGBoost).
• Ability to work autonomously and lead technical direction in ambiguous, high-impact domains.
• Experience collaborating with cross-functional teams including ML scientists, engineers, and product partners.
• Ability to bridge engineering and science teams, and influence technical strategy across disciplines.
• Numerically-savvy and smart with ability to operate at a fast pace
• Master’s degree or PhD in a quantitative discipline, or equivalent additional professional experience. 

Preferred Qualifications

• Practical experience optimizing ML workflows using CUDA/GPU acceleration.
• Background in feature store design, embedding architecture, or synthetic data generation for model training.
• Proven track record of improving model accuracy in production environments with measurable business outcomes.
• Familiarity with modern experimentation frameworks, hyperparameter tuning tools, and automated model selection techniques.

Benefits:

• Comprehensive Healthcare Benefits
• 401k Matching
• Workspace benefits for your home office
• Personal & Professional development funds
• Family Planning Support
• Flexible Vacation (please use them!) & Reddit Global Wellness Days
• 4+ months paid Parental Leave
• Paid Volunteer time off

#LI-Remote

Reddit has a flexible first workforce!

The Ads Measurement Org is dedicated to enhancing the efficiency and user-friendliness of our advertising platform. The Measurement Modeling team owns all the Machine Learning solutions for Ads Measurement, including Identity Matching, Identity Graph, Utility Enhancement for Ads Privacy, Modeled Conversion, and new Measurement Modeling Initiative. As critical and complex part, in Identity Modeling, we are building new advanced machine learning solutions, the space resides in intersection of ads stack that interacts with various upstream and downstream systems, it serves critical business needs for monetization and consumer as well, including Measurement & Reporting, Experimentation, Personalization, Delivery, and Safety etc, requires major XFN as well as cross team/org collaborations.

We are looking for an IC5 Staff ML Engineer of Ads Identity Modeling, to define long term direction and drive architecture evolution, be responsible for engineering quality and enforce best practice, lead new exploration and cross-org collaboration in new modeling initiatives, and champion ML/AI innovation to ensure the solutions utilize SOTA ML technology. Our diverse group of engineers, product managers, data scientists, and ads specialists is excited to welcome you on board!

Minimum Qualifications:

• 7+ years of professional software engineering experience, with at least 3+ years focused on ML-driven systems at scale
• Demonstrated experience architecting and building ads measurement modeling solutions leveraging advanced machine learning techniques
• Strong knowledge of various identifiers (cookies, hashed emails, phone numbers, IP addresses, user agents) and their use in identity resolution
• Proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch) and libraries for feature engineering, model training, and inference
• Solid understanding of large-scale data processing, distributed computing, and data infrastructure (e.g., Spark, Kafka, Beam, Flink)
• Proven technical leadership in cross-functional settings, driving architectural decisions and influencing stakeholders (product, data science, privacy, legal)
• Excellent communication, mentoring, and collaboration skills to align teams on a long-term vision for identity resolution

Responsibilities:

• Lead the technical strategy and architecture for our company’s ads identity modeling solutions and other related ads measurement models
• Design and train advanced ML models while ensuring accuracy, scalability, and compliance with privacy requirements, managing trade-offs between complexity, latency, and prediction quality
• Oversee end-to-end ML workflows—from data ingestion and feature engineering to model training, evaluation, and deployment—optimizing for performance and cost
• Partner with cross-functional teams (e.g., product management, data science, platform engineering, privacy, legal) to define the roadmap and set long-term goals
• Establish engineering best practices, code quality standards, and data governance guidelines to ensure maintainability and trustworthiness of the identity graph
• Mentor and coach junior engineers, fostering a culture of innovation, technical excellence, and knowledge sharing across the organization

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave 

#LI-AK1

The GenAI Security team within Reddit’s Security, Privacy, Assurance, and Corporate Engineering organization protects Reddit’s GenAI usage across employee tools, internal agents, and production user-facing systems. Our mission is to secure and protect Reddit’s AI traffic and GenAI adoption by default.

We are building zero-trust, defense-in-depth systems that verify identity, permissions, data access, and semantic intent across AI workflows. A core part of this work is developing practical, high-quality ML models that detect and prevent security risks such as prompt injection, jailbreak attempts, sensitive data exfiltration, unsafe model behavior, anomalous usage, and unauthorized agent actions.

We are looking for a Senior Machine Learning Engineer to lead model development for GenAI Security and help establish strong ML practices across SPACE. This role owns the full machine learning lifecycle: problem definition, data ETL, feature engineering, model training, model evaluation, deployment, experimentation, prediction, monitoring, debugging, and retraining.

What You’ll Do

• Build and improve security-focused ML models for Reddit’s GenAI traffic, including guardrail models, semantic classifiers, anomaly detection models, and other neural network based security signals.
• Own model development end to end: define the security problem, assemble and label datasets, build ETL pipelines, engineer features, train models, evaluate quality, deploy to production, monitor performance, and retrain from production feedback.
• Use modern deep learning architectures, including neural networks, transformers, sequence models, embeddings, and model distillation where they are the right practical fit.
• Design rigorous evaluation suites for adversarial examples, hard negatives, long-context inputs, structured payloads, tool calls, multi-turn workflows, and real production traffic.
• Improve model precision, recall, latency, cost, calibration, and operational reliability for high-impact production surfaces.
• Build repeatable MLOps workflows for SPACE, including training pipelines, model lineage, artifact management, holdout evaluation, dashboards, rollback paths, and retraining loops.
• Partner closely with ML Infrastructure, LLM Gateway, DevX, Ads, Answers, Safety, Privacy, Compliance, and other Security teams to bring security models into real production workflows.
• Work pragmatically with Reddit’s evolving ML platform, using existing infrastructure where possible and building focused tooling when needed to keep model iteration moving.
• Translate security goals into measurable model outcomes and help partners understand tradeoffs between risk reduction, latency, false positives, and product impact.
• Provide technical direction to other engineers and serve as a go-to ML expert for GenAI Security and broader SPACE model needs.

Who You Might Be

• 5+ years of experience building, training, evaluating, and deploying production ML or deep learning models.
• Hands-on experience with modern ML frameworks such as PyTorch, TensorFlow, or similar.
• Strong practical understanding of the full ML lifecycle: problem definition, data ETL, feature engineering, training, evaluation, deployment, monitoring, debugging, and retraining.
• Experience building data pipelines and working with large-scale datasets.
• Experience designing rigorous model evaluations, including precision/recall/F1, false positive analysis, threshold tuning, calibration, holdout sets, regression tests, and production-quality validation.
• Experience shipping production-quality software, preferably in Python and/or Go.
• Strong communication skills and ability to explain model behavior, risk tradeoffs, and technical decisions to cross-functional partners.
• BS degree in Computer Science, Machine Learning, a related technical field, or equivalent practical experience.
• Experience in the following areas is a plus:
  • Applying ML to security, privacy, trust and safety, abuse prevention, adversarial ML, or GenAI security problems.
  • Training or fine-tuning neural text models for complex inputs such as long-context prompts, structured payloads, code-like content, multi-turn interactions, or tool calls.
  • Production MLOps or model serving systems such as Airflow, Ray, MLflow, Triton, ONNX, Kubernetes, or similar.
  • Improving model quality through labeling strategy, hard-negative mining, synthetic data generation, distillation, or active learning.

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave  

#LI-remote

Ads Content Understanding (ACU) is Reddit’s core commercial content understanding team for Ads. The team owns and produces signals that describe what Reddit content is about, how brand safe and suitable it is, and what users are trying to accomplish in commercial conversations. ACU is responsible for:

• The Knowledge Graph (entities, brands, products, and relationships across Reddit and external sources).
• Content taxonomies such as IAB, Shopify Standard Product Taxonomy, IAS, and other commercial taxonomies used for targeting, safety, and marketplace dynamics.
• Opinion mining for ads use cases: sentiment, stance, commercial intent, and other qualitative attributes of conversations.
• Shopping / product understanding: detecting product entities, product categories, and product attributes in organic conversations and aligning them with shopping catalogs.
• Signals and tags registry: a unified, governed catalog of ACU signals that powers retrieval, ranking, safety, and insights across Ads Foundations and partner teams. 

We are looking for a Staff Machine Learning Engineer who will lead the Commercial Content Understanding roadmap for the Monetization org and act as the technical owner for ACU’s signals and ML systems. Roughly 50% of their time should be spent in technical leadership and mentorship (driving designs, standards, cross-team alignment), and 50% in direct hands-on work (modeling, pipelines, and debugging complex production systems). 

Responsibilities:

• Provide technical leadership and mentorship to MLEs and SWEs doing ML work in ACU, acting as de facto tech lead for content understanding and signals: driving design reviews, setting technical standards, and uplifting the team’s modeling and systems craft.
• Develop evaluation systems and quality monitoring systems for content understanding signals, using SOTA LM-judge practices. 
• Drive operational excellence for ACU’s ML systems by defining SLOs, alerting, and dashboards for key signals (coverage, latency, precision/recall, cost)
• Build and evolve content understanding capabilities for commercial conversations (e.g., reviews vs. recommendations vs. comparisons vs. Q&A; sentiment and stance; product entities and categories) and operationalize them as robust signals that power contextual and shopping ads, auto-targeting, new formats, and insights products.
• Lead design and implementation of signals pipelines and produce an ACU signals registry. Partner with platform teams and other content understanding teams to ensure efficient, reliable serving at Reddit scale.
• Drive LLM and modern ML best practices within ACU: define when to prompt, finetune, or distill; design evaluation and safety harnesses; and lead at least one major distillation effort to replace external APIs with in-house models.
• Operate across the full ML lifecycle (problem framing, data, modeling, evaluation, deployment, monitoring, and oncall), designing scalable, resilient MLOps pipelines and championing responsible AI (bias, safety, explainability) for ACU’s models and signals in production.

Required Qualifications:

• 7+ years of relevant MLE experience delivering production ML systems (models + pipelines + serving) at scale, ideally in large-scale content understanding domains, or Ads. 
• Demonstrated Staff-level technical leadership: has driven architecture decisions, standards, and design reviews across multiple teams, and has aligned PMs, DSs, and engineers on shared ML systems or platforms without direct people-management authority.
• Excellent communication skills, with the ability to explain complex technical trade-offs to PMs, DSs, and other engineering teams, especially in ambiguous, cross-team problem spaces like Seekers/Searchers monetization. 
• Strong track record building and shipping NLP / Language models / content understanding models to production (e.g., classifiers, encoders, sequence or session models), with clear business outcomes (e.g., CTR/ROAS uplift, safety improvements). Experience with commercial or intent modeling is a strong plus.
• Practical experience using LLMs in production for labeling, evaluation, or distillation (e.g., LM-as-judge, prompt-based classifiers, LLM-generated labels distilled into smaller models), including managing quality, cost, and latency trade-offs.
• Deep experience with PyTorch, TensorFlow, or similar, and production-quality code in Python (and ideally one statically typed language like Go/Java/C++). Comfortable owning training, evaluation, and deployment code end-to-end.
• Experience designing ML systems and pipelines: offline training, feature pipelines (batch/streaming), online serving, monitoring, and experimentation for high-traffic surfaces.

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave 

#LI-Remote

Who We Are: 
The Machine Learning Platform team at Reddit is a high-impact team that owns the infrastructure that powers recommendations, content discovery, user and content quantification, while directly impacting other teams such as Growth, Ads, Feeds, and Core Machine Learning teams.

What You’ll Do:
As a Senior Software Engineer, you will lead the development of a large-scale GenAI Platform at Reddit.

• Contribute to the design, implementation, and maintenance of the LLM Gateway, focusing on features like unified API endpoints for internal/externally hosted LLM, rate/token limit management, and intelligent failover mechanisms to boost uptime and reliability.
• Designed and developed ML and Generative AI systems in cloud-based production environments at scale.
• Build and manage enterprise-grade RAG applications using embeddings, vector search, and retrieval pipelines.
• Implement and operationalize agentic AI workflows with tool use using frameworks such as LangChain and LangGraph.
• Drive adoption of MLOps / LLMOps practices, including CI/CD automation, versioning, testing, and lifecycle management.
• Establish best practices for observability, monitoring, evaluation, and governance of GenAI pipelines in production.
• Strong ownership mindset and platform thinking.
• Ability to lead AI platform delivery from concept to production.

Who You Might Be:

• 5+ years of experience in ML Engineering, AI Platform Engineering, or Cloud AI Deployment roles.
• Have experience operating orchestration systems such as Kubernetes at scale
• Deep experience with cloud-based technologies for supporting an ML platform, including tools like AWS, Google Cloud Storage, infrastructure-as-code (Terraform), and more
• Proficiency with the common programming languages and frameworks of ML, such as Go, Python, etc.
• Excellent communication skills with the ability to articulate technical AI concepts to non-technical stakeholders
• Strong focus on scalability, reliability, performance, and ease of use. You are an undying advocate for platform users and have a deep intuition for the genAI product development lifecycle.
• Strong knowledge of model serving, inference pipelines, monitoring, and observability for AI systems is a plus
• Strong proficiency in Python and experience with modern AI/ML frameworks (e.g. LangChain, Vertex AI Agent Builder, TensorFlow, PyTorch is a plus

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave 

The Search Recommendations & Relevance team at Reddit is building the next generation of search - one that goes beyond “10 blue links” to deliver real answers, perspectives and conversation from the world's largest corpus of human conversation. We power both Reddit Search and our AI-native Search experience, redefining how users discover and interact with information.

Redditors produce the most amazing content about every niche topic in the world – this underleveraged data coupled with modern advances in AI systems is presenting a unique opportunity to quickly build a new kind of search engine. As a Senior Staff, you will design and build a large-scale system that powers end-to-end search relevance at scale. You’ll  work across multiple areas of the stack, including query understanding, retrieval, ranking, features, measurement, LLM-based answers, RAG etc, partnering deeply with product, org leads, and other XFN to deliver reliable, high quality systems that can help Reddit Search scale to billions of users.

What You’ll Do

• Contribute to advancing Reddit's Search and Recommendations products by designing AI-driven Search experience prioritizing seamless and delightful user experience. 
• Deeply understand the Reddit search product and drive the vision for the search relevance team.
• Enhance core search retrieval and ranking, design and implement new search engine features,  build and scale search indexes, develop and test new pipeline components.  You will also deploy  ML models, integrate LLMs, and ensure robust monitoring and smooth product integration throughout the process.
• Collaborate across disciplines and with ML, Product, Infrastructure, and DS teams at Reddit to find technical solutions to complex challenges.
• Mentor and guide senior and staff engineers in the team.
• Influence org-wide technical direction and partner closely with senior leadership to shape the long-term roadmap

Who You Are

• 10+ years of industry experience with deep expertise in large-scale search and recommendation systems. 
• Proven ability to identify key opportunities, define roadmaps and drive scalable improvement in  search relevance.
• Strong experience in building and deploying large-scale ML models using frameworks such as PyTorch or Tensorflow.
• Experience working with LLM in production, including evaluation, tuning and deployment.
• In-depth knowledge and experience working with lexical and semantic retrieval systems.
• Proficiency in object-oriented programming (Python, Golang).
• Nice to have: experience building production Agentic AI frameworks.

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave 

#LI-remote, #LI-JS5

Reddit’s lower funnel business is rapidly growing and pushing the heavy ranking web conversion models towards state-of-the-art is critical for continued growth. The Conversion modeling Team plays a pivotal role in developing and maintaining machine learning models that drive user conversions from Reddit Ads, with a special focus on predictive modeling around interactions like purchase, signup, add to cart, and other lower funnel user actions. 

As we expand our machine learning infrastructure and incorporate new engagement signals, we are looking for a skilled Engineering Manager who can lead this critical team. This role is well-suited for a leader with deep machine learning expertise, strategic vision, and a collaborative mindset to engage with both technical and cross-functional stakeholders.

We’re a remote-friendly company, and this position is open to candidates anywhere in the U.S.

Target Skills and Expertise

The Engineering Manager (EM) will be responsible for defining the team’s vision, setting strategic direction, and executing a technical roadmap for conversion modeling at Reddit. This involves:

• Model Architectures: Expertise in architecting and implementing deep learning models, with experience in ranking, recommendation, or conversion modeling.
• ML Frameworks: Proficiency with mainstream ML libraries (TensorFlow, PyTorch).
• End-to-End ML Lifecycle: Experience in training, testing, and deploying production-grade machine learning models.
• Data Pipelines: Experience orchestrating large-scale data generation and processing pipelines.
• Ads domain Experience: Experience in interaction of ranking model with rest of Ads systems like bidding, auction, retrieval etc
• Ads Modeling (Preferred): Background in ads modeling or familiarity with engagement prediction models in the ads domain is beneficial.

Role responsibilities:

The EM will lead a diverse, high-impact team and will need to navigate and foster collaboration with various teams such as PM, DS, and engineering functions within Ads. Ideal candidates will have:

• People Management Experience: Prior experience managing engineering teams with a strong emphasis on technical mentorship and team growth.
• Set Technical Vision and Strategy: Ability to plan and execute a long-term technical strategy aligned with business objectives. Define and execute a roadmap for conversion modeling, balancing innovative modeling approaches with business objectives.
• Drive Technical Execution: Oversee the model development lifecycle from ideation to deployment, ensuring high standards of ML performance and robustness.
• Lead and Mentor a High-Performing Team: Recruit, mentor, and retain top ML talent, fostering a culture of growth, collaboration, and technical excellence.
• Collaborate Cross-Functionally: Partner with PMs, data scientists, and other engineering teams to align on engagement strategies, data requirements, and model KPIs.
• Innovate in ML Architecture: Implement and optimize model architectures tailored to conversion prediction, leveraging deep learning and advanced ML techniques.

Required qualifications:

• At least 2+ of experience building and managing high-performing machine learning teams, ideally in the Ads domain. Will consider tech lead experience as well
• Deep ML Expertise: Deep hands-on experience working with machine learning models and deploying them in large-scale production systems.  Proven ability in training, evaluating, and deploying large-scale models.
• Technical Domain Knowledge:  Experience with Ads conversion modeling, ranking (heavy ranker experience) & recommendations experience is required. 
• Strategic Thinking: Ability to develop and communicate a clear, compelling technical strategy that supports broader company objectives and addresses the needs of internal customers.
• Impact-Driven Mindset: Passion for developing scalable, well-designed, and responsible AI solutions that drive business value.
• Exceptional Communication & Collaboration: Strong interpersonal skills and a collaborative mindset, with the ability to effectively communicate complex technical topics to diverse audiences and build strong relationships with cross-functional partners

Experience with Ads conversion modeling is a plus

Perks and Benefits:

• 100% remote opportunity (we have 4 office locations for hybrid/onsite work preference in NY, SF, LA and Chicago)
• Competitive salary and equity options
• Comprehensive health benefits (medical, dental, vision) & workplace perks (home office set up stipend etc)
• Generous 401k matching
• Flexible vacation policy 
• Paid parental leave (4+ months)
• Family planning support
• Paid volunteer time off

#LI-AS1

WHAT YOU’LL DO

• Guide DSP engineers in the execution of DSP trade studies and optimization of signal processing and machine learning algorithms for deployment on FPGAs and GPUs.
• Collaborate with a multidisciplinary team of software and hardware engineers to develop software defined radios; and direct DSP team in the engagement with the software & hardware team, including the implementation of DSP techniques into software and firmware and integration activities.
• Design and implement algorithms and techniques for RADAR systems
• Develop Modeling and Simulation (M&S) code for RADAR techniques and data analysis including Hardware-in-the Loop / Software-in-the-loop (HIL/SIL) testing
• Participate in laboratory and field testing of RF systems and techniques
• Participate in the maturation of RF systems into deployable systems and products

REQUIRED QUALIFICATIONS

• 7+ years with a BSEE or related field 
• Strong experience with DSP implementation for embedded devices and/or software defined radios.
• Strong knowledge of Python and MATLAB. Experience with CUDA or GPU accelerated frameworks like cuSignal is preferred.
• Experience with embedded devices, including FPGA, Nvidia Jetson, and Software Defined Radios.
• Skilled with Modeling and Simulation of RF systems including Radar and SAR
• Familiar with deep learning algorithms. Experience with ML frameworks such as TensorFlow and PyTorch is a plus.
• Familiar with wireless communication standards (Bluetooth, 3G/4G/5G, Wi-Fi, SINCGARS, MUOS, etc.).
• Excellent at balancing multiple projects at any given time and/or managing a larger team for a larger program.
• Enthusiastic about both working with a team and executing some work individually (depending on program scope).
• Experience with Electronic Warfare systems.
• Some travel required.
• Currently possesses and is able to maintain an active U.S. Secret security clearance.

PREFERRED QUALIFICATIONS

• Masters or PhD degree in Electrical, Electronics, Computer Engineering, or related fields
• Defense, national security, or aerospace domain familiarity through industry or education.
• Extensive Digital Signal Processing (DSP) knowledge and experience
• Expertise in Synthetic Aperture Radar (SAR) and/or Inverse SAR (ISAR): Image formation, waveforms, phenomenology, modeling and simulation

ABOUT THE TEAM

Anduril Maritime delivers platforms, systems, and integrated effects in the maritime domain. Our autonomous vehicles (sub-surface and surface) are the cornerstone of these capabilities, and we continually strive to push the boundaries of the possible in terms of endurance, autonomy and mission capability. The Maritime team develops and maintains core products and payloads, and adapts and applies those products to serve a wide variety of defense, IC and commercial customers in US and international markets.

ABOUT THE JOB 

We are seeking a Senior Machine Learning/MLOps Engineer to join the Applied Intelligence team within Maritime Digital Production. You will lead the design, deployment, and sustainment of the AI-enabled backbone that connects data, tools, and people across our digital shipbuilding environment. This role focuses on operationalizing advanced models and architecting the industrial AI stack—selecting, integrating, and standardizing technologies that bring intelligence into production systems only where they deliver real value.

You’ll define and implement core components of the platform, including unified data and feature stores, vector databases, orchestration layers, and model-serving frameworks, while integrating off-the-shelf models for computer vision, OCR/IDP, speech, and retrieval-augmented generation. You’ll work across software, data, manufacturing, and corporate technology teams to translate real factory scenarios—inspection, root-cause analysis, receiving workflows, scheduling—into applied AI capabilities with clear human-in-the-loop controls, auditability, safety gates, and integrations with PLM, MES, CMMS, ERP, and the unified data plane.

This role demands technical range, judgment, and an instinct for when AI is the right tool versus when a simpler logic or workflow solution wins. You’ll collaborate across Anduril in a high-tech, fast-paced culture of innovation focused on delivering systems that work in the real world. If you want to shape how AI becomes a practical, reliable tool for production and logistics at scale, you’ll be helping build the future of digital shipbuilding and the next generation of maritime vehicles.

WHAT YOU’LL DO 

• Architect and own the AI/ML platform stack—from data ingestion, labeling, and feature engineering to model training, deployment, monitoring, and lifecycle management.
• Select, prioritize, and standardize industrial AI components including feature stores, vector databases + RAG, OCR/IDP and CV/STT providers, orchestration layers, and observability systems.
• Build model-serving and inference frameworks optimized for production environments, supporting real-time and batch execution across cloud, edge, and shop-floor systems.
• Translate factory scenarios (receiving, inspection, RCCA, scheduling) into applied AI workflows with defined human-in-the-loop gates, audit trails, and integration contracts with PLM, MES, CMMS, ERP, and the unified data plane.
• Implement event-driven data pipelines and telemetry systems that feed models with contextualized, real-time signals from production and logistics systems.
• Drive make/buy strategy by researching internal and vendor AI capabilities and recommending investments aligned to enterprise roadmaps, Anduril IP principles, and production constraints.
• Define and maintain model governance processes for validation, safety reviews, traceability, and rollback.
• Partner with Maritime platform teams and CorpTech to align architectures with enterprise data standards, ontologies, and compliance policies.
• Lead reliability engineering for deployed models—managing drift detection, retraining triggers, alerting, and operational SLOs.
• Mentor junior engineers and data scientists; establish best practices for MLOps, observability, data management, and secure handling of sensitive production data.

REQUIRED QUALIFICATIONS 

• Strong stakeholder management skills with proven experience aligning engineering, data, and manufacturing teams.
• 8+ years of experience in software or ML engineering with end-to-end delivery of production-grade AI/ML systems.
• Deep experience with MLOps: data acquisition, labeling, curation, pipeline management, model versioning, continuous integration, and model monitoring.
• Strong proficiency in Python and experience with deep learning frameworks (PyTorch, TensorFlow).
• Experience building and deploying containerized ML services using Docker and Kubernetes.
• Proficiency in data engineering, time-series data modeling, and working with semantic/ontology-driven data systems.
• Experience implementing observability for model performance, inference accuracy, and data drift.
• Familiarity with event-driven architectures, IoT/UNS patterns, and real-time systems integration.
• Excellent communication and documentation abilities; able to bridge research, platform, and production domains.
• Eligible to obtain and maintain an active U.S. Secret security clearance.

PREFERRED QUALIFICATIONS 

• Experience applying AI/ML within manufacturing, logistics, industrial control, or production environments.
• Background with digital twins, predictive maintenance, OCR/IDP, CV, or STT model integrations.
• Experience with workflow/orchestration tools such as Flyte, Airflow, Kubeflow, or Temporal.
• Familiarity with GPU acceleration (CUDA) and inference optimization (TensorRT, Triton).
• Experience in regulated environments (NNPI/ITAR) and secure model/data governance.
• Demonstrated ability to mentor engineers and set technical direction for AI/ML infrastructure at scale.

WHAT YOU’LL DO

• Design, develop, and optimize digital signal processing (DSP) algorithms and systems for radio direction finding and direction-of-arrival (DoA) estimation in defense applications.  
• Collaborate with a multidisciplinary team of software and hardware engineers to develop software defined radios; and direct DSP team in the engagement with the software & hardware team, including the implementation of DSP techniques into software and firmware and integration activities.
• Implement high-performance, real-time signal processing chains on embedded and hardware platforms to support mission-critical sensing capabilities.  
• Develop Modeling and Simulation (M&S) code for RADAR techniques and data analysis including Hardware-in-the Loop / Software-in-the-loop (HIL/SIL) testing
• Participate in laboratory and field testing of RF systems and techniques
• Participate in the maturation of RF systems into deployable systems and products

REQUIRED QUALIFICATIONS

• 5+ years with a BSEE or related field
• Strong foundation in digital signal processing, comms theory, & system engineering with emphasis in direction finding algorithm implementation
• Hands-on experience with direction finding, angle-of-arrival estimation, and multi-antenna signal processing.  
• Strong experience with DSP implementation for embedded devices including FPGA, Nvidia Jetson, and Software Defined Radios and/or software defined radios.
• Strong knowledge of Python and MATLAB. Experience with CUDA or GPU accelerated frameworks like cuSignal is preferred.
• Skilled with Modeling and Simulation of RF systems including Radar and SAR
• Familiar with deep learning algorithms. 
• Familiar with wireless communication standards (Bluetooth, 3G/4G/5G, Wi-Fi, SINCGARS, MUOS, etc.).
• Enthusiastic about both working with a team and executing some work individually (depending on program scope).
• Experience with Electronic Warfare systems.
• Currently possesses and is able to maintain an active U.S. Secret security clearance.

PREFERRED QUALIFICATIONS

• Masters or PhD degree in Electrical, Electronics, Computer Engineering, or related fields
• Experience with ML frameworks such as TensorFlow and PyTorch 
• Defense, national security, or aerospace domain familiarity through industry or education.
• Extensive Digital Signal Processing (DSP) knowledge and experience
• Expertise in Synthetic Aperture Radar (SAR) and/or Inverse SAR (ISAR): Image formation, waveforms, phenomenology, modeling and simulation

ABOUT THE TEAM

Anduril Labs is a multidisciplinary team of technologists, solution architects, engineers, and military subject matter experts. Its mission is to drive innovation across all Anduril business units and product lines by developing novel concepts and next-generation technologies that enhance Anduril’s competitive edge and give its customers a decisive technological advantage over its adversaries.

ABOUT THE JOB

We are looking for a talented full stack software engineer to join our growing team at Anduril Labs in Washington, DC. As a full stack software engineer in Anduril Labs, you will help bring innovative, next-generation concepts to life through proof-of-concept development and rapid prototyping using bleeding edge technologies.

The ideal candidate has exceptional software development and creative problem-solving skills, is a self-starter, and can quickly grasp complex concepts. As a full stack software engineer, you possess the skills to architect, develop, and deploy distributed applications and services, including both front-end and back-end components. You have experience with agile, end-to-end software development lifecycle and are comfortable developing and deploying code across Windows and Linux-based systems (including standalone bare-metal hardware, virtualized environments, and cloud-hosted platforms). Embedded software development experience is a plus. You are also proficient in integrating legacy code and systems, leveraging open-source technologies, and developing and utilizing APIs. Additionally, you have a solid understanding of AI/ML core concepts (e.g., feature extraction, supervised vs. unsupervised learning, regression, classification, clustering, deep learning neural networks, NLP, LLMs, SLMs, model fine-tuning, prompt engineering, RAG) and hands-on experience developing (Gen)AI-enhanced applications or services.

We also expect candidates to have familiarity with database technologies (e.g., SQL, NoSQL, Graph DB, Vector DB) and experience with data modeling, data wrangling, analytics, and visualization. Since Anduril Labs supports all Anduril businesses and product lines, you will have the unique opportunity to work closely with multi-disciplinary engineering and product development teams across the entire company. This means you will get to directly contribute to the development of Anduril’s next-generation products and services. So if you thrive in a dynamic environment that values creative problem-solving, love writing code, excel as both an individual contributor and team player, are eager to learn, and bring a can-do attitude, this role is for you.

WHAT YOU’LL DO

• Lead the development of prototypes to demonstrate advanced concepts in areas like autonomous and multi-agent systems, GenAI, advanced data analytics, quantum computing/sensing/networking/comms/machine learning, modeling, simulation, optimization, visualization, next-gen human-machine interfaces, heterogenous computing, and cybersecurity.
• Own the entire Software Development Lifecycle from inception through development, testing, deployment, and documentation for Anduril Labs-developed software prototypes.
• Interface and collaborate with other Anduril and customer engineering teams, and strategic partners.
• Support Anduril- and customer-funded R&D efforts.
• Participate in field experiments and technology demonstrations.

REQUIRED QUALIFICATIONS

• 3+ years of programming with Python, C++, Java, Rust, Go, or JavaScript/TypeScript.
• Proven software architecture and design skills.
• Ability to quickly understand and navigate complex systems and established codebases.
• AI/ML development using commercial and open-source AI frameworks, models, and tools (e.g., Jupyter Notebook, PyTorch, TensorFlow, Scikit-learn, OpenAI, Claude, Gemini, Llama, LangChain, YOLO, AWS Sagemaker, Bedrock, Azure AI, RAG).
• Web app development (e.g., React, Angular, or Vue).
• Cloud development (e.g., AWS, Azure, or GCP).
• Data modeling and wrangling.
• Networking basics (e.g., DNS, TCP/IP vs. UDP, socket communications, LDAP, Active Directory)
• Database technologies (e.g., SQL, NoSQL, Graph DB, Vector DB).
• API development and integration (e.g., REST, GraphQL).
• Containerization technologies (e.g., Docker, Kubernetes).
• Software development on Linux and Windows.
• Demonstrable hands-on experience using GenAI tools (e.g., OpenAI Codex, Claude Code, Gemini Code Assist, GitHub Copilot, Amazon CodeWhisperer, or similar) for software development, code generation, debugging, and algorithmic exploration.
• Experience with Git version control, build tools, and CI/CD pipelines.
• Demonstrated understanding and application of software testing principles and practices, including unit testing, integration testing, and end-to-end testing.
• Strong problem-solving skills, meticulous attention to detail, and the ability to work effectively in a collaborative team environment.
• Excellent communication and interpersonal skills, with the ability to effectively articulate complex technical concepts to diverse audiences.
• Eligible to obtain and maintain an active U.S. Top Secret SCI security clearance

PREFERRED QUALIFICATIONS

• BS in Computer Science, Engineering, or similar field.
• Distributed applications development (e.g., client/server, microservices, multi-agent solutions).
• High performance computing (HPC) and big data technologies (e.g., Apache Spark, Hadoop).
• Mobile app development (e.g., iOS or Android).
• Embedded software development experience.
• Willingness to travel up to approximately 10%

ABOUT THE TEAM

Anduril’s Tactical Recon & Strike (TRS) is a division with two missions: 1) build highly capable autonomous drones, and 2) build solid rocket motors at scale. We transform products like Ghost, Anvil, Bolt, and Altius from early concepts into fully operational capabilities by partnering closely with specialist engineering, operations, and production teams. Through our Anduril Rocket Motor Systems (RMS) team, we design and manufacture solid rocket motors using advanced materials, proprietary formulations, and high-volume production methods—delivering safe, reliable propulsion systems that support a wide range of mission requirements. TRS hires software engineers & hardware engineers, who are excited to build across a diverse and powerful portfolio—from autonomous aerial systems to high-performance solid rocket motors. Our teams contribute to highly capable autonomous robotics systems and propulsion products that operate reliably in the most demanding mission environment.

ABOUT THE JOB

We are seeking Senior Software Engineers specializing in Computer Vision and Machine Learning Engineering. You will leverage cutting-edge research to solve our most challenging perception problems for our UAVs, bringing deep expertise in Object Detection, Object Tracking, or related perception domains. This role requires hands-on proficiency in C++ and/or Python within a Linux environment. If you are passionate about tackling complex technical challenges in computer vision and perception, we encourage you to apply.

This position will be located at our headquarters in Costa Mesa, CA (relocation benefits provided).

WHAT YOU’LL DO

• Propose and prototype innovative solutions to solve real world problems, leveraging the latest state-of-the-art techniques in the field.
• Develop and maintain core libraries and runtime applications.
• Integrate classical and geometric methods in computer vision with ML methods.
• Work with ML and Data Infra team to construct various benchmarks for analyzing system performance.

REQUIRED QUALIFICATIONS

• MS or PhD in Machine Learning, Robotics or Computer Science, with emphasis on Computer Vision.
• BS in Computer Science, Machine Learning, Electrical Engineering, or related field.
• 4+ years experience developing and benchmarking ML algorithms on large-scale datasets.
• High proficiency in C++ development in a Linux environment.
• Experience deploying models with TensorRT and ONNX.
• Experience with Python development and deep learning frameworks such as PyTorch and TensorFlow.
• Experience writing and maintaining automated continuous integration tests.
• Experience in one or more of the following:
• Object Detection, Object Tracking, Instance Segmentation, Semantic Segmentation, Semantic change Detection.
• Experience in one or more of the following:
• Visual Odometry, SLAM, Multi-view Geometry, Structure from Motion, 3D Geometry, Discriminative Correlation Filters, Stereo, Neural 3D Reconstruction, RGB-D and LIDAR Sensor Fusion.
• Eligible to obtain and maintain an active U.S. Secret security clearance.

PREFERRED QUALIFICATIONS

• Experience troubleshooting and analyzing remotely deployed software systems.
• Proficient in Python.
• Proficient in CUDA.

WHAT YOU’LL DO

• Design and implement algorithms and techniques for RADAR systems
• Develop Modeling and Simulation (M&S) code for RADAR techniques and data analysis including Hardware-in-the Loop / Software-in-the-loop (HIL/SIL) testing
• Guide DSP engineers in the execution of RADAR-DSP trade studies and optimization of signal processing and machine learning algorithms for deployment on FPGAs and GPUs.
• Participate in laboratory and field testing of RADAR-EW systems and techniques
• Participate in the maturation of RADAR-EW systems into deployable systems and products

REQUIRED QUALIFICATIONS

• Experience with Electronic Warfare systems.
• Experience with DSP algorithms and technique development for RADAR- Electronic Support Measures (ESM) and Electronic Counter Measure (ECM) systems.
• Strong experience with DSP implementation for embedded devices and/or software defined radios.
• Skilled with Modeling and Simulation of RF systems including Radar and SAR
• Strong knowledge of Python and MATLAB.
• Excellent at balancing multiple projects at any given time and/or managing a larger team for a larger program.
• Enthusiastic about both working with a team and executing some work individually (depending on program scope).
• Some travel required.
• Currently possesses and is able to maintain an active U.S. Secret/Top Secret security clearance.

PREFERRED QUALIFICATIONS

• Masters or PhD degree in Electrical, Electronics, Computer Engineering, or related fields.
• Experience with CUDA or GPU accelerated frameworks like cuSignal.
• Familiar with deep learning algorithms. Experience with ML frameworks such as TensorFlow and PyTorch is a plus.
• Experience with embedded devices, including FPGA, Nvidia Jetson, and Software Defined Radios.
• Expertise in Synthetic Aperture Radar (SAR) and/or Inverse SAR (ISAR): Image formation, waveforms, phenomenology, modeling and simulation.

WHAT YOU’LL DO

• Guide DSP engineers in the execution of DSP trade studies and optimization of signal processing and machine learning algorithms for deployment on FPGAs and GPUs.
• Collaborate with a multidisciplinary team of software and hardware engineers to develop software defined radios; and direct DSP team in the engagement with the software & hardware team, including the implementation of DSP techniques into software and firmware and integration activities.
• Design and implement algorithms and techniques for RADAR systems
• Develop Modeling and Simulation (M&S) code for RADAR techniques and data analysis including Hardware-in-the Loop / Software-in-the-loop (HIL/SIL) testing
• Participate in laboratory and field testing of RF systems and techniques
• Participate in the maturation of RF systems into deployable systems and products

REQUIRED QUALIFICATIONS

• 7+ years with a BSEE or related field 
• Strong experience with DSP implementation for embedded devices and/or software defined radios.
• Strong knowledge of Python and MATLAB. Experience with CUDA or GPU accelerated frameworks like cuSignal is preferred.
• Experience with embedded devices, including FPGA, Nvidia Jetson, and Software Defined Radios.
• Skilled with Modeling and Simulation of RF systems including Radar and SAR
• Familiar with deep learning algorithms. Experience with ML frameworks such as TensorFlow and PyTorch is a plus.
• Familiar with wireless communication standards (Bluetooth, 3G/4G/5G, Wi-Fi, SINCGARS, MUOS, etc.).
• Excellent at balancing multiple projects at any given time and/or managing a larger team for a larger program.
• Enthusiastic about both working with a team and executing some work individually (depending on program scope).
• Experience with Electronic Warfare systems.
• Some travel required.
• Currently possesses and is able to maintain an active U.S. Secret security clearance.

PREFERRED QUALIFICATIONS

• Masters or PhD degree in Electrical, Electronics, Computer Engineering, or related fields
• Defense, national security, or aerospace domain familiarity through industry or education.
• Extensive Digital Signal Processing (DSP) knowledge and experience
• Expertise in Synthetic Aperture Radar (SAR) and/or Inverse SAR (ISAR): Image formation, waveforms, phenomenology, modeling and simulation

Why You'll Love This Role

You will work closely with the founding team and a group of highly-skilled engineers to shape the future of AI-enabled Security/Observability platforms. You will play a central role in bringing integrating cutting-edge AI/ML technologies to the Cribl Product suite to help solve real customer problems.  You will work closely with development partners and key stakeholders to iteratively design, develop, and deliver products and surfaces that will delight our customers.

On top of it all you will have fun. Cribl strives to be a great place to work for everyone.

As An Active Member Of Our Team, You Will...

• Design, train, and evaluate machine learning models across a range of research and applied AI initiatives
• Run rapid, iterative experiments to test hypotheses and surface insights that drive model improvements
• Collaborate closely with researchers and engineers to translate cutting-edge academic advances into practical, production-ready systems
• Build and maintain robust ML pipelines for data ingestion, feature engineering, model training, and evaluation
• Optimize model performance through fine-tuning, hyperparameter search, and architecture experimentation
• Contribute to a culture of rigorous experimentation; tracking results, documenting findings, and sharing learnings with the broader team
• Stay current with the latest developments in ML and AI research, and proactively identify opportunities to apply them
• This position may require stand-by, on-call, or off-hours duties during critical research or deployment milestones

If You've Got It - We Want It

• Bachelor's degree in Computer Science, Mathematics, Statistics, or a related field with 5+ years of industry or research experience (Master's or PhD a plus)
• Deep hands-on experience training and evaluating ML models, including language models
• Strong proficiency in Python and ML frameworks such as PyTorch or TensorFlow
• Familiarity with MLOps tooling and infrastructure (e.g., MLflow, Weights & Biases, Kubeflow, or similar)
• Solid understanding of modern NLP, computer vision, and/or reinforcement learning techniques
• Strong ability to move fast without sacrificing rigor; you know when to prototype and when to productionize
• Excellent communication skills with the ability to clearly present experimental results to both technical and non-technical stakeholders

Salary Range ($230,000 - $275,000)

The salary for this role is dependent on geographic location. The salary offered within the range described will be based on the individual candidate’s job-related knowledge, skills, and experience.  In addition to a competitive salary, Cribl also offers a generous benefits package which includes health, dental, vision, short-term disability, and life insurance, paid holidays and paid time off, a fertility treatment benefit, 401(k), equity, and eligibility for a discretionary company-wide bonus.

#LI-JB1
#LI-Remote

Location

Palo Alto, CA

Job Description

Rhombus’ Data Engineers are instrumental in designing and implementing data engineering activities on topical, mission-driven projects that inform our national security agenda. They analyze, build, and maintain our organization’s data infrastructure and processing systems. 

Additionally, our Data Engineers perform various code development and query needs for integration with new and existing applications, dashboards and machine learning pipelines. Our Data Engineers work cross functionally with other departments to meet business needs. They utilize their skills at all stages of the analytics pipeline to create results that drive business values and customer success.

Responsibilities:

• Develop code using various programming and scripting languages to automate data ingestion and improve data management processes.
• Architect data repositories, stand up data platforms and develop data pipelines for ingestion, transformation, and aggregation.
• Review existing architecture, data strategy, and improve processes for data governance, data quality, and metadata management.
• Extract and analyze raw data from multiple data sources via APIs, SQL Stored Procedures, or Python scripts.
• Ability to develop scripts and programs for converting various types of data into usable formats and support project team to scale, monitor and operate data platforms.
• Collaborate with a multi-disciplinary team of analysts, data scientists, data engineers, developers, and data consumers in a fast-paced, agile environment.
• You’ll use your experience in analytical exploration and data examination while you manage the assessment, design, building, and maintenance of scalable platforms for clients.
• Communicate project status and results to various levels of leadership.

Qualifications:

• At minimum Bachelor’s degree in Data Analytics, Computer Science, Computer Engineering, Information Systems/Sciences, or other relevant area (or equivalent experience) and at least 3 years of professional experience, or a Master’s degree with strong academic project experience and one year of work experience.  
• Experience with 1 or more programming and scripting languages, with a strong focus on Python, Pandas and Numpy. Other languages include: Shell, PERL, Java, C/C++/C#, Scala, etc.
• Experience with 1 or more of the following relational, noSQL and/or file based storage (e.g. MYSQL, MongoDB, SQL Server, Oracle, Postgres, Hbase, DynamoDB, etc.)
• Experience building and maintaining ETL data pipelines
• Experience with software development life cycle including testing, documenting, delivery and support
• Working knowledge of AWS/cloud technologies
• Experience using query optimization as well as data modeling techniques.
• Familiarity with machine learning frameworks (such as TensorFlow, Scikit-Learn, etc.)

Personal Qualities:

• Bias for action: Rhombus seeks ‘doers’ who will get things done with accuracy, speed and at scale.
• Ability to contextualize data as it relates to Rhombus’ vision. We want someone who can understand the “why” and “so what”, and not just the “how”. Our Data Engineers help us transmit the enthusiasm we have around the data work to the individuals doing that work.
• Must have strong problem-solving skills and demonstrated excellent oral and written communication skills.
• We’re seeking folks with strong intellectual curiosity and creativity, with an ability and willingness to learn new skills and apply novel solutions to problems.
• Comfort in a fast-paced start-up environment is crucial, with the ability to consistently revise your approach in response to new information, and to be flexible and adaptive.

Salary Range

• The estimated base salary range for this position is $110,000 to $180,000/year

Benefits 

• Full medical, dental, vision coverage for employee and dependents 
• 401k matching program 
• PTO and Holidays 
• Bonus and other incentive programs
• Access to mental health program
• Access to Flexible Spending Accounts for Health Care, Dependent and Commuter

About Rhombus 

Rhombus Power Inc. (Rhombus) is a startup located in the heart of Silicon Valley at Stanford Research Park in Palo Alto.  We use cutting-edge cross-disciplinary approaches to solve pressing Big Data and Sensing problems in security, energy, and healthcare. Our advisory board includes two Nobel Laureates and a Draper Prize winner. 

Rhombus compensates, motivates, and develops employees, who are trusted, empowered, and involved. Employees have clear roles and expectations – and their roles are flexible enough to move at the speed of innovation in order to meet and exceed client expectations. We have a unique culture of global purpose, rooted in the innovation and progress of Silicon Valley. 

Rhombus knows that diversity is a condition for success. We are committed to hiring and retaining a diverse workforce. We are proud to be an Equal Opportunity/Affirmative Action Employer. 

What You Will Learn:

• Real-world ML benchmarking workflows from model to hardware.
• Performance tuning and optimization techniques.
• How ML applications are tested, validated, and productized.
• Collaboration across software, hardware, and research teams.

Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.

Tenstorrent is seeking an Physical Design Engineer to lead  cross-functional efforts to solve complex physical design challenges and develop end-to-end RTL-to-GDS methodologies across advanced nodes, with a strong focus on PPA and runtime improvements. The engineer will architect, integrate, and deploy AI/ML-driven solutions into production physical design flows, creating custom CAD tools and partnering with internal teams and EDA vendors to drive next-generation, ML-enabled capabilities. 

This role is hybrid, based out of Santa Clara, CA or Austin, TX or Fort Collins, CO.

We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting.

Who you are

• BS in Electrical or Computer Engineering (or equivalent experience) with 5+ years in Physical Design CAD methodology at advanced nodes.
• Proven track record improving PPA and/or runtime on high-performance, low-power taped-out designs.
• Hands-on with industry-standard EDA tools (e.g., Fusion Compiler) across synthesis, P&R, STA, signoff, and hierarchical flows.
• Strong Python/Tcl and data skills, with interest or experience in ML frameworks (PyTorch, TensorFlow), and the ability to drive complex projects independently.

What we need

• Lead and contribute to cross-functional efforts solving complex physical design challenges across IPs, projects, and advanced technology nodes.
• Develop and enhance RTL-to-GDS methodologies, including floorplanning, synthesis, P&R, STA, signoff, and assembly.
• Architect and deploy AI/ML-driven solutions in production flows to improve engineering efficiency, turnaround time, and QoR.
• Optimize EDA tools and custom CAD flows using data-driven and ML-based techniques, in close collaboration with verification, extraction, timing, DFT, and EDA vendors.

What you will learn

• How to scale AI/ML-driven methodologies across diverse products and advanced technology nodes in real production flows.
• New ways to blend classical EDA algorithms with modern ML techniques to push PPA and runtime limits.
• Best practices for deploying, validating, and monitoring ML models in production CAD environments.
• How to influence next-generation ML-enabled EDA tools and collaborate deeply with cross-functional teams (PV, extraction, timing, DFT).

Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made.

Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.

This position requires access to technology that requires a U.S. export license for persons whose most recent country of citizenship or permanent residence is a U.S. EAR Country Groups D:1, E1, or E2 country. 

• Leadership to drive compiler development across multiple layers of the stack, including custom dialects, transformation passes, and runtime integration.
• Alignment with hardware, software, and ML teams to ensure the compiler supports realistic performance and deployment needs.
• Technical ownership of roadmap priorities, planning, and mentorship for a high-performing engineering team.
• Insight to identify bottlenecks, debug performance issues, and improve developer workflows across the stack.

• Experience building compilers or similar systems, with strong fluency in C++ and Python.
• Strong knoweledge of MLIR, LLVM, or related infrastructure, with hands-on work in dialect design or optimization passes.
• You have a strong understanding of modern AI frameworks like PyTorch, TensorFlow, or JAX, including how models are transformed and executed.
• A background in working across teams to ship reliable, scalable tools in fast-paced engineering environments.

• How to build compiler infrastructure that supports both training and inference at scale across custom chip architectures.
• New approaches for human-in-the-loop optimization using TT-Explorer and other internal tooling.
• Best practices for evolving MLIR dialects like TTIR, TTNN, and TTKernel to support next-generation AI workloads.
• How Tenstorrent delivers open, performant, and developer-friendly AI infrastructure that scales with industry demands.

Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made.

Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.

Join the team revolutionizing AI computing at Tenstorrent. You'll work on TT-Forge, our MLIR-based compiler that enables developers to run AI on all configurations of Tenstorrent hardware using an open-source, performant, and general-purpose compiler. You will be at the forefront of the AI hardware revolution, building compiler technologies that redefine what’s possible.

 This role is hybrid, and can be based out of Santa Clara, CA; Austin, TX; or Toronto; ON.

We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting.

Who You Are

• A passionate software engineer eager to work on compiler technologies and the challenges of AI hardware, whether from compilers, systems, or broader software backgrounds.
• Fluent in C++ and Python, with experience building complex systems that bridge high-level frameworks to low-level execution.
• Excited by compiler optimization and machine learning, with experience in PyTorch, JAX, TensorFlow, or deep systems programming.
• A collaborative problem-solver who thrives in open-source and enjoys working closely with hardware and software engineers.

What We Need

• A drive to solve novel challenges in AI compilation, from optimizing computational graphs to creating custom dialects and transformation passes.
• Experience or strong interest in MLIR and how modular compiler frameworks connect AI models to advanced hardware.
• Motivation to build technology that impacts the future of AI, knowing your work will enable the next wave of breakthroughs.

What You Will Learn

• How to build open-source compiler frameworks supporting diverse AI models and workloads, including training and multi-chip scaling.
• Deep expertise in compiler technologies including custom MLIR dialects (TTIR, TTNN, TTKernel) and transformation passes.
• New methods for human-in-the-loop compiler optimization using TT-Explorer, making advanced tuning tools usable by all developers.
• How compiler technology powers Tenstorrent’s mission to deliver affordable, open-source AI computing in a highly competitive space.

Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made.

Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.

We’re looking for a Field Application Engineer who’s wired for AI/ML, fluent in real-world problem-solving, and excited to build with the people actually using what we make. You will collaborate closely with the sales team and enterprise customers, leveraging your deep technical knowledge in AI to drive the adoption of our products and solutions. This is a customer-facing role that requires both technical expertise and excellent communication skills to convey complex technical concepts to non-technical stakeholders.

This role is hybrid, based out of Santa Clara, CA.  

We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting.

Who You Are

• You’ve lived in the AI/ML trenches, whether as a field engineer, a solutions architect, or the one tapped in when things needed to “just work.”
• You speak both machine and human. Whether it’s a researcher or a skeptical executive, you know how to break things down and bring them to life.
• You’re fired up about generative models, LLMs, and the edge of what’s possible when software meets purpose-built silicon.
• Work directly with customers in meetings, presentations, and workshops to understand their technical challenges and provide effective solutions.
• Partner closely with sales operations and product teams to provide feedback from customers and help shape future product enhancements.

What We Need

• Strong customer-facing skills with 5+ years of relevant technical, enterprise experience (such as Sales Engineer, Solutions Engineer, or Technical Account Manager).
• Your field insight will help shape our roadmap, our features, and the way we show up for developers.
• Proven expertise in AI technologies and frameworks, including machine learning, deep learning, natural language processing (NLP),computer vision, PyTorch or TensorFlow.
• Experience with embedded systems, FPGA Architecture or AI accelerators. Familiarity with hardware/software co-optimization is often critical for efficient inference at the edge.
• Good understanding of data center, server architecture and deployment, thermal/power, and infrastructure management.

What You Will Learn

• How to explore and push the boundaries of AI performance on custom silicon and help developers do the same.
• What it’s like to build the future from scratch, working alongside teams creating hardware, software, and everything in between.
• To master the craft of fine-tuning LLMs, optimizing vision models, and building AI pipelines that run at scale.
• An understanding of why field roles drive real impact turning on-the-ground insight into product breakthroughs and platform momentum.

Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made.

Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.