Staff ML Systems Engineer

GM • Sunnyvale, CA

1d • Hybrid

About The Position

Help teach our self-driving vehicles how to see and understand the world! The Data Labeling Engineering team designs, builds, and operates hybrid human/machine data labeling tools and pipelines that power autonomous vehicle machine learning models within General Motors' AV organization. We operate at the intersection of software engineering, data engineering, and AI/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 full-stack architecture including TypeScript/React, Python, GraphQL, Golang, and ML model services, which powers data-annotation pipelines and machine-led training data solutions at foundation-model scale. We partner closely across AI/ML engineers, Product Operations, Product Management, Data Science, and other ML Platform groups. This role is ideal for an engineer looking for end-to-end ownership of meaningful pieces of the platform, growth in technical and strategic leadership, and direct impact across teams and systems that unblock the next generation of AV capabilities.

Requirements

• 8+ years of experience building robust distributed platforms and applications
• Hands-on experience leveraging AI tools (agentic workflows, knowledge acquisition, documentation generation, operational triage, etc) to accelerate understanding, implementation, debugging, and delivery of new capabilities
• Proficiency in writing and reviewing high‑quality, scalable, and performant full-stack code using technologies and languages like Python, TypeScript, Go, React, SQL, Redux, gRPC, GraphQL, WebGL, etc
• Solid understanding of scalable software system design including data modeling and API/interface design
• Strong fundamentals in object‑oriented design and design patterns, data structures, algorithms, and engineering best practices (TDD, code quality, observability, CI/CD)

Nice To Haves

• A track record of close collaboration with customers, product managers, designers, and/or user experience researchers
• Experience with computer vision, machine learning, or data-centric AI projects — especially where data annotation, data quality, or autolabeling loops were central to the work
• Familiarity with data labeling/annotation platforms or tools used by large labeling workforces (e.g., annotation UIs, workflow engines, quality systems)
• Experience with A/B testing and telemetry/observability systems to measure impact and reliability
• Experience developing data-intensive or visualization‑heavy applications

Responsibilities

• Define the platform vision and roadmap
• Own projects end‑to‑end
• Collaborate across the AV stack
• Level up how ML teams work with data
• Apply ML to labeling itself
• Build high‑impact labeling experiences
• Champion AI‑assisted engineering

Benefits

• medical
• dental
• vision
• Health Savings Account
• Flexible Spending Accounts
• retirement savings plan
• sickness and accident benefits
• life insurance
• paid vacation & holidays
• tuition assistance programs
• employee assistance program
• GM vehicle discounts

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed