ML Data Labeling Engineer — Build AutoML Tools

generalmotors; Sunnyvale (CA); Hybrid; USD 125,000 - 165,000; Full time

Job summary

General Motors' Data Labeling Engineering team seeks an early-career Software Engineer to build tools and services for autonomous driving data pipelines. You will work across frontend and backend, collaborating with ML engineers and ops to deliver scalable labeling solutions.

You will learn from experienced engineers, contribute to production systems, and develop depth across frontend, backend, data, and ML-adjacent technologies while shipping features impacting labeling quality and model

Qualifications

• Recent graduate within 12 months of graduation in CS/CE/AI or related STEM field.
• Experience shipping software or features via internships, research, or projects.
• Proficiency in Python, TypeScript, JavaScript, Go, Java, or C++.
• Strong OO design, data structures, APIs, and engineering best practices.
• Clear communication and collaboration with cross-functional partners.
• Interest in autonomous vehicles, robotics, ML, or ML platform tech.

Responsibilities

• Build tools and services for labeling workflows and data quality.
• Collaborate with ML engineers on ML-driven data annotation features.
• Design scalable frontend experiences and backend services for labeling.
• Promote AI-assisted engineering and modern development workflows.

Skills

Python

TypeScript

JavaScript

Go

Java

C++

Education

Bachelor's or Master's in Computer Science/Engineering/AI (within 12 months of graduation)

Tools

GraphQL

React

SQL

gRPC

WebGL

Redux

Job description

General Motors' Data Labeling Engineering team seeks an early-career Software Engineer to build tools and services for autonomous driving data pipelines. You will work across frontend and backend, collaborating with ML engineers and ops to deliver scalable labeling solutions.

You will learn from experienced engineers, contribute to production systems, and develop depth across frontend, backend, data, and ML-adjacent technologies while shipping features impacting labeling quality and model