Hybrid ML Systems Engineer - Labeling & Data Tools

General Motors; Mountain View (WY); Hybrid; USD 90,000 - 192,000; Full time

Benefits offered by this job

Health benefits

Relocation assistance

Vehicle discounts

Job summary

General Motors is seeking a Data Labeling Engineer to help build and operate high‑quality labeling tools and pipelines for autonomous vehicle ML models. You will work at the intersection of software, data engineering, and ML, shaping labeling strategies, tooling, and data quality at scale.

You’ll own end-to-end projects, ship features for labeling data in new models and cities, and collaborate with ML Engineers, Ops, Product, and Data Science teams to hit quality, cost, and latency goals.

Qualifications

• Passionate about self-driving technology.
• Learn new technologies across frontend, backend and data/ML systems.
• Proven experience shipping and operating end-to-end products in production.
• Strong communication and collaboration skills in cross-functional teams.
• Empathetic to user challenges and able to turn workflows into simple tools.
• 2+ years of experience building robust web applications.
• Bachelor's degree or higher in CS or related field.

Responsibilities

• Build high-impact labeling experiences using modern full-stack/front-end technologies.
• Develop automation and tooling to improve labeling workflows and data quality.
• Collaborate with ML engineers to apply ML-driven data annotation techniques.
• Own technical projects from problem framing to rollout, including reviews and design decisions.
• Collaborate with AV stack partner teams to meet quality, cost, and latency goals.
• Advocate for AI-assisted engineering and modern development workflows.

Skills

Self-driving tech interest

Frontend & Backend

Production shipping

Communication & collaboration

User-centric design

Education

Bachelor's degree in CS or related field

Tools

TypeScript

React

Redux

GraphQL

WebGL

Airflow

Cloud platforms

Job description

General Motors is seeking a Data Labeling Engineer to help build and operate high‑quality labeling tools and pipelines for autonomous vehicle ML models. You will work at the intersection of software, data engineering, and ML, shaping labeling strategies, tooling, and data quality at scale.

You’ll own end-to-end projects, ship features for labeling data in new models and cities, and collaborate with ML Engineers, Ops, Product, and Data Science teams to hit quality, cost, and latency goals.