ML Systems Engineer - Labeling & AI Tools for AVs

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

Benefits offered by this job

Health and wellbeing programs

GM vehicle discounts

Job summary

General Motors’ Data Labeling Engineering team is building cutting‑edge labeling tools and pipelines that power autonomous vehicle ML models. The role sits at the intersection of software, data engineering, and ML, focusing on scalable labeling systems and foundations for foundation‑model scale.

You’ll collaborate with ML engineers, Operations, Product Management, Data Science, and other GM platform groups to ship end‑to‑end labeling features and enable AI‑assisted engineering across the stack.

Qualifications

• 2+ years of experience building robust web applications.
• Bachelor's degree or higher in Computer Science or related field, or relevant work experience.
• Hands-on experience leveraging AI tools (agentic coding, search, documentation generators).
• Proficiency in writing high-quality, scalable, and performant code using TypeScript, React, GraphQL, WebGL, or similar frontend technologies.

Responsibilities

• Build high‑impact labeling experiences using modern full‑stack/frontend technologies.
• Level up ML data workflows with automation and tooling to improve data quality and efficiency.
• Apply ML to labeling through pre-labeling, autolabeling, and active learning loops.
• Own projects end‑to‑end from design to rollout, including reviews and technical decisions.
• Collaborate across the AV stack with ML, Ops, Product, Data Science, and other platform teams to achieve quality, cost, and latency goals.
• Champion AI‑assisted engineering to accelerate development while maintaining quality.

Skills

TypeScript

React

GraphQL

Python

Golang

Airflow

AI tooling

Education

Bachelor's degree in Computer Science or related field

Tools

Airflow

Job description

General Motors’ Data Labeling Engineering team is building cutting‑edge labeling tools and pipelines that power autonomous vehicle ML models. The role sits at the intersection of software, data engineering, and ML, focusing on scalable labeling systems and foundations for foundation‑model scale.

You’ll collaborate with ML engineers, Operations, Product Management, Data Science, and other GM platform groups to ship end‑to‑end labeling features and enable AI‑assisted engineering across the stack.