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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # ML Systems Engineer, Data Labeling Engineering - Early Career - **Company:** General Motors - **Location:** Sunnyvale, CA, United States - **Salary:** $125,000.0 - $165,000.0 - **Contract:** Internship / Graduate position - **Skills:** Training Data, Java (Programming Language), JavaScript (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, C++ (Programming Language), Software Quality, Computer Programming, Computer Engineering, Continuous Integration, Data Structures, Software Debugging, Software Design Patterns, Design of User Interfaces, Python (Programming Language), Machine Learning, Azure Machine Learning, Software Engineering, SQL Databases, TypeScript, WebGL, ReactJS, Backend, Build Tools, Graphql, Machine Learning Operations, Front End Software Development, React Redux, Grpc, Data Pipelines, Golang - **Published:** September 11, 2026 - **Apply:** https://dejobs.org/x/x/3BD850F686754D36B3A9CE324DF64BA6/job/ ## About the Role * Recentlycompleted a bachelor's, master's, 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. * Experience shipping software or features through internships, research, academic projects, orpriorprofessional work. * Programming experience in one or more languages such as Python, TypeScript, JavaScript, Go, Java, or C++. * Familiarity with software fundamentals, including o bject-oriented design, design patterns, data structures, algorithms, API/interface design , and engineering best practices. * Strong communication and collaboration skills; you can explain tradeoffs, influence peers, and work through ambiguity with cross-functional 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 experience leveraging AI tools (agentic workflows, knowledge acquisition, documentation generation, operational triage,etc) to accelerate understanding, implementation, debugging, and delivery of new capabilities. * Proficiencyin 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). * Driven to learn new technologies and deepen yourexpertiseacross frontend, backend, and data/ML-adjacent systems. * Empathetic to user challenges (from labelers to ML engineers to Ops) and excited to turn messy workflows into simple, intuitive tools . ## Description 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 * 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, auto-QA, autolabel review tools), reducing iteration time from idea to trained model. * Apply ML to labeling itself Collaborate with ML engineers to design and integrate ML-driven data annotation (pre-labeling,autolabeling, active learning loops), helping us move from human-only to machine-led labeling at scale. * Build high - impact labeling experiences Design, implement, and test scalable, high-performance user experiences and services using modern full-stack and/or frontend technologies.You'llship 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 AI-powered development workflows (code assistants, automated documentation, test generation, etc.) to increase build-velocity whilemaintainingcode and product quality. ## Related Videos - [How Machine Learning is turning the Automotive Industry upside down](https://www.wearedevelopers.com/videos/61-how-machine-learning-is-turning-the-automotive-industry-upside-down) - [Go with the Flow: Stop the Leaks Before Your Memory's a Waterfall!](https://www.wearedevelopers.com/videos/100073-go-with-the-flow-stop-the-leaks-before-your-memory-s-a-waterfall) - [Rendering Design Software in the Browser at Penpot](https://www.wearedevelopers.com/videos/1353-rendering-design-software-in-the-browser-at-penpot) - [Exploring the Power of gRPC-Gateway for Writing RESTful Services](https://www.wearedevelopers.com/videos/2072-exploring-the-power-of-grpc-gateway-for-writing-restful-services) - [What non-automotive Machine Learning projects can learn from automotive Machine Learning projects](https://www.wearedevelopers.com/videos/397-what-non-automotive-machine-learning-projects-can-learn-from-automotive-machine-learning-projects) - [Scoring 2000 Products per Request: Performance Pitfalls in Golang](https://www.wearedevelopers.com/videos/2073-scoring-2000-products-per-request-performance-pitfalls-in-golang) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [How software is steering vehicle technology](https://www.wearedevelopers.com/magazine/515-how-software-is-steering-vehicle-technology) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [What Jobs Can You Get with a Software Engineering Degree?](https://www.wearedevelopers.com/magazine/398-what-jobs-can-you-get-with-a-software-engineering-degree) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Why Upskilling And Reskilling is Important For Developers](https://www.wearedevelopers.com/magazine/428-why-upskilling-and-reskilling-is-important-for-developers)