Senior ML Systems Engineer — AV Platform (Remote)

General Motors; Sunnyvale, Northern (CA, KY); Hybrid; USD 172,000 - 304,000; Full time

Benefits offered by this job

Health benefits

GM vehicle discounts

Tuition assistance

Job summary

General Motors is seeking a Staff ML Systems Engineer to help our Data Labeling Engineering team advance self-driving vehicle capabilities. You will own end-to-end platform projects, define roadmaps, and work across ML, data science, and product teams to deliver scalable labeling workflows and AI-assisted tooling.

The role emphasizes cloud-scale, distributed systems, modern full-stack development, and collaboration with cross-disciplinary teams to ship high-impact features for AV data annotation

Qualifications

• 8+ years of experience building distributed platforms and applications.
• Hands-on experience leveraging AI tools to accelerate capability delivery.
• Proficiency with Python, TypeScript, Go, React, SQL, Redux, gRPC, GraphQL, WebGL.
• Strong understanding of scalable software design, data modeling, APIs.

Responsibilities

• Define the platform vision and roadmap across cross-functional teams.
• Own projects end-to-end from problem framing to rollout.
• Collaborate with ML Engineering, Operations, Product, Data Science to implement workflows and APIs.
• Develop automation/tools to improve labeling workflows and data quality.
• Apply ML to labeling to enable machine-led labeling at scale.
• Build scalable user experiences and services across frontend/backend stacks.
• Champion AI-assisted engineering and modern development workflows.

Skills

Python

TypeScript

Go

React

SQL

Redux

gRPC

GraphQL

WebGL

Tools

SQL databases

Job description

General Motors is seeking a Staff ML Systems Engineer to help our Data Labeling Engineering team advance self-driving vehicle capabilities. You will own end-to-end platform projects, define roadmaps, and work across ML, data science, and product teams to deliver scalable labeling workflows and AI-assisted tooling.

The role emphasizes cloud-scale, distributed systems, modern full-stack development, and collaboration with cross-disciplinary teams to ship high-impact features for AV data annotation