ML Systems Engineer, Data Labeling Engineering - Early Career
Core
Build tools, services, and pipelines that enable ML teams to create high-quality training data for autonomous driving, including automation, quality systems, and ML-integrated annotation workflows.
Role type
Early-career full-stack software engineer (data labeling platform)
Builds
Data annotation pipelines, ML-integrated labeling tools, efficiency dashboards, and quality control systems for autonomous vehicle training data
Domain
Autonomous vehicles / AI/ML data infrastructure
Deliverable
production ML models
Required skills
Python, TypeScript, JavaScript, Go, Java, C++, object-oriented design, data structures, algorithms, API/interface design, software fundamentals
Preferred skills
AI tooling (agentic workflows, documentation generation), scalable full-stack code, system design, TDD, CI/CD, observability
Technologies
TypeScript, React, Python, GraphQL, Golang, Redux, gRPC, WebGL, SQL
Responsibilities
Develop automation and tooling for labeling workflows and data quality; Design and integrate ML-driven data annotation (pre-labeling, autolabeling); Build scalable user experiences and services for labeling platforms; Advocate for AI-powered development workflows
Seniority
Junior, hands-on IC
