ML Systems Engineer
Job Summary
The Data Labeling Engineering team at General Motors is seeking an ML Systems Engineer to build hybrid human/machine labeling tools and pipelines that power autonomous vehicle machine learning models. You will design scalable full-stack experiences, develop automation to improve data quality, and integrate ML-driven data annotation at scale. This hybrid role requires collaboration across cross-functional teams to unblock the next generation of AV models.
Responsibilities
- Build scalable labeling experiences and services
- Develop automation and tooling for ML data workflows
- Integrate ML-driven data annotation and active learning
- Own technical projects end-to-end
Required Skills
- 2+ years building robust web applications
- Proficiency in TypeScript, React, GraphQL, and modern web tech
- Strong fundamentals in data structures, algorithms, and API design
- Experience with cloud-based applications and AI tools
Job Details
What You'll Do
- Build high-impact labeling experiences: Design, implement, and test scalable, high-performance user experiences and services using modern full-stack and/or frontend 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.
- Apply ML to labeling itself: Collaborate with ML engineers to design and integrate ML-driven data annotation (pre-labeling, autolabeling, active learning loops).
- Own projects end-to-end: Take ownership of technical projects from problem framing through design, implementation, and rollout.
- Collaborate across the AV stack: Work with partner teams to translate abstract requirements into concrete workflows, APIs, and UIs.
- Champion AI-assisted engineering: Use and advocate for modern AI-powered development workflows.
Your Skills & Abilities (Required Qualifications)
- General: Passionate about self-driving technology, driven to learn new technologies, proven experience shipping end-to-end products, strong communication skills, and empathetic to user challenges.
- Technical: 2+ years of experience building robust web applications. Bachelors degree or higher in Computer Science or related field (or relevant work experience). Hands-on experience leveraging AI tools. Proficiency in TypeScript, React, Redux, GraphQL, WebGL, or similar frontend technologies. Solid understanding of relational databases, data modeling, and API design. Strong fundamentals in object-oriented design, data structures, algorithms, and engineering best practices. Experience developing and operating cloud-based applications. Experience with A/B testing and telemetry/observability systems.
What Will Give You a Competitive Edge (Preferred Qualifications):
- 4+ years of experience in software development.
- Experience using modern web APIs in data-intensive or visualization-heavy applications.
- Track record of close collaboration with customers, product managers, designers, and user experience researchers.
- Experience with computer vision, machine learning, or data-centric AI projects.
- Familiarity with data labeling platforms or tools used by large labeling workforces.