✦ Luna Orbit — AI & Machine Learning

Staff AI/ML Fullstack Engineer - AV ML Infra

at General Motors

📍 Sunnyvale, California, United States of America Unknown 💰 $218K – $335K USD / year Posted March 20, 2026
Salary $218K – $335K USD / year
Type Not Specified
Experience mid
Exp. Years Not specified
Education Not specified
Category AI & Machine Learning

This role involves designing and building end-to-end AI/ML infrastructure for autonomous vehicles, supporting simulation, inference, and scalable ML experimentation.

  • Design and develop ML infrastructure
  • Support simulation workloads
  • Build scalable backend services
  • Collaborate with product teams
  • Mentor junior engineers

The environment includes cloud platforms, ML tools, simulation workloads, and system design for autonomous vehicle AI systems.

The ideal candidate is a full-stack engineer with experience in building scalable AI/ML infrastructure, familiar with simulation workloads, inference pipelines, and cloud platforms, capable of leading complex projects in autonomous vehicle technology.

Full-Stack DevelopmentAPIscloud infrastructureML infrastructuresystem design
ML platformssimulation workloadsML inference pipelinesML trainingdata science
Cloud platformsML toolsSimulation tools
Full-Stack DevelopmentAPIscloud infrastructureML infrastructuresimulation workloadsML inference pipelinesML trainingdata sciencesystem designautonomous vehicles
Full-Stack DevelopmentWeb ApplicationsBackend ServicesAPIsCloud InfrastructureML InfrastructureML PlatformsSimulation WorkloadsML Inference PipelinesML ComputeData ScienceSystem Design
collaborationmentoringtechnical depthsystem designproject ownership
Industry Automotive / Mobility / Technology
Job Function Developing AI/ML infrastructure for autonomous vehicle systems
Role Subtype Full Stack Engineer
Tech Domains Active Directory, Microsoft 365, Azure, Amazon Web Services, Kubernetes, Docker, Python, JavaScript, Cloud Platforms, ML Tools
Full-Stack DevelopmentAPIscloud infrastructureML infrastructureML platformssimulation workloadsML inference pipelinesML trainingdata sciencesystem designautonomous vehiclesAI validationML computeML experimentationreproducibilityfull-stack developmentML pipelinesML inference

Lack of experience in ML infrastructure, No experience with cloud platforms, No background in autonomous vehicle systems, Unwillingness to work on complex system design

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