Help teach our self-driving vehicles how to see and understand the world.

TheData Labeling Engineeringteam designs, builds, andoperateshybrid human/machine data labeling tools and pipelines that power autonomous vehicle machine learning models within General Motors' AV organization. Weoperatein the intersection of software engineering,data engineering, andAI/ML, defining the strategies, tooling, and quality controls that create reliable training data at scale. Our tools and platform are used by thousands of users and consumers.

We own a modern fullstack architecture includingTypeScript/React, Python,GraphQL, Golang, andML model services, which powers dataannotation pipelines and machineled training data solutions atfoundationmodel scale. We partner closelyacrossAI/ML engineers,Product Operations,Product Management,Data Science, and otherML

Platformgroups.

As an early-career Software Engineer on the Data Labeling Engineering team, you will build tools and services that help machine learning teams create high-quality training data for autonomous driving. Your work may span frontend experiences, backend services, data pipelines, machine learning integrations, and quality systems used by labelers, ML engineers, and operations teams.

This role is designed for a recent college graduate or engineer early in their careerwho wants to own meaningful pieces of a platform, grow their technicalexpertise, and work directly on systems that enable the next generation of AV capabilities. You will learn from experienced engineers while contributing to production systems and developing depth across frontend, backend, data, and ML-adjacent technologies.

• Level up how ML teams work with data
  Develop automation and tooling that give ML engineers deep insight into labeling workflows and data quality (e.g., efficiency dashboards, autoQA, autolabel review tools), reducing iteration time from idea to trained model.

• Apply ML tolabelingitself
  Collaborate with ML engineers to design and integrate MLdriven data annotation (prelabeling,autolabeling, active learning loops), helping us move from humanonly to machineled labeling at scale.

• Build high-impact labeling experiences
  Design, implement, and test scalable, highperformance user experiences and services using modern fullstack and/or frontend technologies.Youllship features spanning multiplesurface-areasthat directly affect how quickly and accurately we can label data for new models and cities.

• Champion AI-assisted engineering
  Use and advocate for modern AIpowered development workflows (code assistants, automated documentation, test generation, etc.) to increase build-velocity whilemaintainingcode and product quality.

• Recentlycompleted a bachelors, masters, or PhD degree inComputer Science, Computer Engineering, Software Engineering, Artificial Intelligence, Machine Learning, or a relatedSTEM field.For completed degrees, graduation must have occurred within the past12months.

• Experienceshippingsoftware or features through internships, research, academic projects, orpriorprofessional work.

• Programming experience in one or more languages such asPython, TypeScript, JavaScript, Go, Java, or C++.

• Familiarity with software fundamentals, including object-oriented design, design patterns, data structures, algorithms, API/interface design, and engineering best practices.

• Strongcommunicationand collaborationskills; you can explain tradeoffs, influence peers, and work through ambiguity with crossfunctional partners.

• Interestin autonomous vehicles, robotics, machine learning, data-centric AI, or developer and ML platform technologies.

• Degree completedbetween May2025 and August 2026, with availability to begin employment in 2026.

• Hands-on experienceleveragingAI tools(agentic workflows, knowledge acquisition, documentation generation, operational triage,etc) to accelerate understanding, implementation, debugging, and delivery of new capabilities.

• Proficiencyin writing and reviewing highquality, scalable, and performant full-stack code using technologies and languages likePython, TypeScript, Go, React, SQL, Redux,gRPC,GraphQL, WebGL, etc.

• Solid understanding ofscalable software system designincluding data modeling and API/interface design.

• Strong fundamentals inobject-oriented design and design patterns,data structures,algorithms, and engineering best practices (TDD, code quality, observability, CI/CD).

• Driven tolearnnew technologiesand deepen yourexpertiseacross frontend, backend, and data/MLadjacent systems.

• Empathetic to user challenges (from labelers to ML engineers to Ops) and excited to turn messy workflows intosimple, intuitive tools.

• Hybrid:This role is categorized ashybrid. This means the successful candidate is expected to report to ourSuynnvale, CA office three times per week, at minimum.

• This job may be eligible for relocation benefits

Compensation:The compensation information is a good faith estimate only. It is based on what a successful applicant might be paidin accordance withapplicable state laws. The compensation may not be representative for positionslocatedoutside of New York, Colorado, California, or Washington.

• The salary range for thisroleis $125,000 to $165,000. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.

• Bonus Potential: Anincentivepayprogram offers payouts based on company performance, job level, and individual performance.