Software Systems Engineer, Data Labeling Engineering - Early Career

General Motors • Sunnyvale, CA

4d • $125,000 - $165,000 • Hybrid

About The Position

As an early-career Software Engineer on General Motors’ Data Labeling Engineering team, you will build tools and services that help machine learning teams create high-quality training data for autonomous driving. Work may span frontend experiences, backend services, data pipelines, machine learning integrations, and quality systems used by labelers, ML engineers, and operations teams. You will own meaningful pieces of a platform, learn from experienced engineers, contribute to production systems, and develop expertise across frontend, backend, data, and ML-adjacent technologies.

The team designs, builds, and operates hybrid human/machine data-labeling tools and pipelines for autonomous-vehicle machine-learning models. Its platform combines software engineering, data engineering, and AI/ML, and supports thousands of users and consumers. The modern full-stack architecture includes TypeScript/React, Python, GraphQL, Golang, and ML model services. The team partners with AI/ML engineers, Product Operations, Product Management, Data Science, and other ML Platform groups.

The role is hybrid, with the successful candidate expected to report to the Sunnyvale, California office at least three times per week. The position may be eligible for relocation benefits. The stated salary range is $125,000 to $165,000, with incentive pay potential based on company performance, job level, and individual performance.

Requirements

• 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; completed degrees must have been awarded within the past 12 months.
• Experience shipping software or features through internships, research, academic projects, or prior professional work.
• Programming experience in one or more of 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.
• Strong communication and collaboration skills, including explaining tradeoffs, influencing peers, and working through ambiguity with cross-functional partners.
• Interest in autonomous vehicles, robotics, machine learning, data-centric AI, or developer and ML platform technologies.

Nice To Haves

• Degree completed between May 2025 and August 2026, with availability to begin employment in 2026.
• Hands-on experience using AI tools and workflows to accelerate understanding, implementation, debugging, and delivery of new capabilities.
• Proficiency writing and reviewing high-quality, scalable, performant full-stack code using technologies such as Python, TypeScript, Go, React, SQL, Redux, gRPC, GraphQL, and WebGL.
• Solid understanding of scalable software system design, including data modeling and API/interface design.
• Strong fundamentals in object-oriented design, design patterns, data structures, algorithms, and engineering best practices such as TDD, code quality, observability, and CI/CD.
• Motivation to learn new technologies and deepen expertise across frontend, backend, and data/ML-adjacent systems.
• Empathy for user challenges, from labelers to ML engineers to Operations, and enthusiasm for turning messy workflows into simple, intuitive tools.

Responsibilities

• Develop automation and tooling that give ML engineers insight into labeling workflows and data quality, such as efficiency dashboards, auto-QA, and autolabel review tools.
• Collaborate with ML engineers to design and integrate ML-driven data annotation, including pre-labeling, autolabeling, and active-learning loops.
• Design, implement, and test scalable, high-performance user experiences and services using modern full-stack and/or frontend technologies.
• Ship features across multiple product areas that improve the speed and accuracy of labeling data for new models and cities.
• Use and advocate for AI-powered development workflows, such as code assistants, automated documentation, and test generation, while maintaining code and product quality.

Benefits

• Potential eligibility for relocation benefits.
• Incentive pay program with payouts based on company performance, job level, and individual performance.
• Employee well-being support at work and at home, with further details available through GM Total Rewards resources.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level