ML Systems Engineer, Data Labeling Engineering – Early Career

General Motors

Early-career engineer building full-stack data-labeling tools for General Motors’ autonomous vehicle machine-learning systems. Developing annotation workflows, quality automation, and scalable platform services.

Posted 9/9/2026full-timeSunnyvale • California • 🇺🇸 United StatesMid-LevelSenior💰 $125,000 - $165,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in developing automation and tooling for data labeling workflows, with strong programming skills in Python, TypeScript, and JavaScript. Proficient in applying production engineering practices and collaborating with cross-functional teams to enhance data quality and user experiences.

Highest-signal resume keywords

Python ProgrammingTypeScript ProgrammingData Annotation WorkflowsCI/CD PracticesMachine Learning Integration

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

JavaScript ProgrammingGo ProgrammingJava ProgrammingC++ ProgrammingObject-Oriented DesignData StructuresAlgorithmsAPI DesignTest-Driven DevelopmentData Modeling

Soft Skills

Clear CommunicationCollaborative Problem SolvingTechnical Tradeoff ReasoningAdaptability to New Technologies

Tools & Technologies

ReactSQLReduxGRPCGraphQLWebGLObservability SystemsTelemetryA/B TestingVisualization Tools

Industry Keywords

Data-Centric AIAutonomous VehiclesRoboticsData QualityMachine LearningData AnnotationQuality SystemsWorkflow EnginesCross-Functional CollaborationAI-Assisted Engineering

Tech Stack

Tools & technologies

C++GoGraphQLGRPCJavaJavaScriptPythonReactReduxSQLTypeScript

About the role

Key responsibilities & impact

Develop automation and tooling for labeling workflows and data quality, including efficiency dashboards, automated quality assurance, and autolabel review tools
Collaborate with ML engineers to design and integrate ML-driven data annotation, including pre-labeling, autolabeling, and active learning loops
Help evolve labeling workflows from human-only processes toward machine-led labeling at scale
Design, implement, and test scalable, high-performance user experiences and services using modern full-stack and/or frontend technologies
Ship features across multiple product surfaces to improve the speed and accuracy of data labeling for new models and cities
Apply production engineering practices including code review, automated testing, observability, CI/CD, and incremental delivery
Use AI-assisted development workflows such as code assistants, automated documentation, test generation, and operational triage while maintaining code and product quality
Partner with labelers, ML engineers, Product Operations, Product Management, Data Science, and other cross-functional teams to improve the platform

Requirements

What you’ll need

Recently completed a bachelor’s, master’s, or PhD degree in Computer Science, Computer Engineering, Software Engineering, Artificial Intelligence, Machine Learning, or a related STEM field; completed degree must have been awarded within the past 9 months
Experience building software through coursework, internships, research, personal projects, or prior professional experience
Programming experience in one or more of Python, TypeScript, JavaScript, Go, Java, or C++
Familiarity with object-oriented design, design patterns, data structures, algorithms, API/interface design, and engineering best practices
Exposure to building applications, services, data pipelines, or user-facing tools in a collaborative environment
Ability to learn new technologies, reason about technical tradeoffs, and communicate clearly with engineering and cross-functional partners
Interest in autonomous vehicles, robotics, machine learning, data-centric AI, or developer and ML platform technologies
Preferred: graduation between December 2025 and August 2026, with availability to begin employment in 2026
Preferred experience with Python, TypeScript, Go, React, SQL, Redux, gRPC, GraphQL, WebGL, or similar tools
Preferred familiarity with scalable software system design, data modeling, API/interface design, observability, CI/CD, or test-driven development
Preferred experience with computer vision, machine learning, data-centric AI, data annotation, data quality, or autolabeling workflows
Preferred familiarity with data labeling or annotation platforms, annotation user interfaces, workflow engines, or quality systems
Preferred experience with A/B testing, telemetry, observability systems, data-intensive applications, visualization-heavy applications, AI-assisted engineering workflows, and cross-functional collaboration

Benefits

Comp & perks

Potential eligibility for relocation benefits
Incentive pay program with payouts based on company performance, job level, and individual performance
Benefits supporting employee well-being at work and at home
Reasonable accommodations for applicants with disabilities