- Location
- GM Automation - Sunnyvale - GM Automation - Sunnyvale, United States of America
- Workplace
- Hybrid
- Type
- Full-time
- Department
- Engineering
- Education
- PhD
- Closing date
- Oct 9, 2026
- Source
- Workday
Description
Job Description
About the Team
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 work 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. These systems power data-annotation pipelines and machine-led training data solutions at foundation-model scale. We partner closely with AI/ML engineers, Product Operations, Product Management, Data Science, and other ML Platform groups.
About the Role
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 career who wants to own meaningful pieces of a platform, grow their technical expertise, 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.
What You’ll Do
Develop automation and tooling that give ML engineers deep insight into labeling workflows and data quality, including efficiency dashboards, automated quality assurance, and autolabel review tools.
Collaborate with ML engineers to design and integrate ML-driven data annotation, including pre-labeling, autolabeling, and active learning loops.
Help evolve labeling workflows from human-only processes toward machine-led labeling at scale.
Design, implement, and test scalable, high-performance user experiences and services using modern full-stack and/or frontend technologies.
Ship features spanning multiple product surfaces that improve how quickly and accurately teams can label data for new models and cities.
Learn and apply production engineering practices, including code review, automated testing, observability, CI/CD, and incremental delivery.
Use and contribute to modern AI-assisted development workflows, such as code assistants, automated documentation, test generation, and operational triage, while maintaining code and product quality.
Partner with labelers, ML engineers, Product Operations, Product Management, Data Science, and other cross-functional teams to understand user needs and improve the platform.
Basic Qualifications
Recently completed a bachelor’s, master’s, or PhD degree in Computer Science, Computer Engineering, Software Engineering, Artificial Intelligence, Machine Learning, or a related STEM field. For completed degrees, graduation must have occurred within the past 9 months.
Experience building software through coursework, internships, research, personal projects, or prior professional experience.
Programming experience in one or more languages such as Python, 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.
Exposure to building applications, services, data pipelines, or user-facing tools in a collaborative environment.
Ability to learn new technologies, reason about technical tradeoffs, and communicate clearly with engineering and cross-functional partners.
Interest in autonomous vehicles, robotics, machine learning, data-centric AI, or developer and ML platform technologies.
Preferred Qualifications
Graduation between December 2025 and August 2026, with availability to begin employment in 2026.
Experience shipping software or features through internships, research, academic projects, or prior professional work.
Experience with technologies such as Python, TypeScript, Go, React, SQL, Redux, gRPC, GraphQL, WebGL, or similar tools.
Familiarity with scalable software system design, data modeling, API/interface design, observability, CI/CD, or test-driven development.
Experience with computer vision, machine learning, or data-centric AI projects, especially projects involving data annotation, data quality, or autolabeling workflows.
Familiarity with data labeling or annotation platforms, including annotation user interfaces, workflow engines, or quality systems.
Experience with A/B testing, telemetry, or observability systems used to measure product impact and reliability.
Experience developing data-intensive or visualization-heavy applications.
Familiarity with AI-assisted engineering workflows, including agentic development, knowledge acquisition, documentation generation, debugging, or operational triage.
Experience collaborating with customers, product managers, designers, or user experience researchers.
Passion for self-driving and robotics technology and its potential to transform safety, mobility, and the human experience.
Location:
Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report to our Suynnvale, 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 paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of New York, Colorado, California, or Washington.
The salary range for this role : is $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: An incentive pay program offers payouts based on company performance, job level, and individual performance.
About GM
Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.
Why Join Us
We believe we all must make a choice every day – individually and collectively – to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.
Benefits Overview
From day one, we're looking out for your well-being–at work and at home–so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources.
Non-Discrimination and Equal Employment Opportunities (U.S.)
General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.
All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws.
We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire.
Accommodations
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