Early-Career Data Labeling Platform Engineer

General Motors Company; Sunnyvale (CA); Hybrid; USD 125,000 - 165,000; Full time

Benefits offered by this job

Relocation benefits

Job summary

General Motors Company in Sunnyvale, CA is seeking an early-career Software Engineer on the Data Labeling Engineering team to build tools and services for ML training data in autonomous driving. You will work across frontend, backend, data pipelines, and ML-adjacent systems to enable scalable labeling workflows.

You will learn from experienced engineers, own meaningful pieces of a platform, and contribute to production systems, with opportunities to grow in full-stack capabilities and

Qualifications

• Recently completed a degree in CS/CE/SE/AI/ML within the last 12 months or soon after.
• Experience shipping software via internships, research, or projects.
• Proficient in Python, TypeScript, JavaScript, Go, Java, or C++ and related tooling.
• Strong fundamentals in OOD, data structures, algorithms, and API design.
• Excellent communication, collaboration, and ability to work with cross-functional partners.
• Interest in autonomous vehicles, robotics, ML, and data-centric AI.

Responsibilities

• Build tools and services across frontend, backend, data pipelines, and ML integrations for labeling at scale.
• Collaborate with ML engineers to design ML-driven data annotation and auto-labeling features.
• Develop scalable, high-performance user experiences and services that improve labeling workflows.
• Promote AI-powered development workflows to increase velocity while ensuring quality.

Skills

Programming languages

Communication skills

Collaboration

Interest in AV/ML

Education

Bachelor's degree or higher in CS/CE/SE/AI/ML

Tools

Python

TypeScript

Go

React

GraphQL

gRPC

Job description

General Motors Company in Sunnyvale, CA is seeking an early-career Software Engineer on the Data Labeling Engineering team to build tools and services for ML training data in autonomous driving. You will work across frontend, backend, data pipelines, and ML-adjacent systems to enable scalable labeling workflows.

You will learn from experienced engineers, own meaningful pieces of a platform, and contribute to production systems, with opportunities to grow in full-stack capabilities and