Principal ML Tech Lead Manager - Embodied AI Onboard Autonomy

What You'll Do

• Define and drive the technical vision and architecture for trajectory generation systems used in autonomous driving.
• Lead the development of ML-based trajectory generation models capable of handling complex and dynamic driving environments.
• Arcitect scalable training pipelines using large-scale driving datasets and simulation environments.
• Guide the integration of trajectory generation models into real-time onboard systems with strict latency and safety requirements.
• Influence the design of next-generation embodied AI architectures for driving.
• Mentor senior engineers and help develop the next generation of technical leaders.
• Raise the bar for engineering excellence, modeling rigor, and production-quality systems.
• Foster a culture of innovation, ownership, and collaborative problem solving.
• Lead complex technical initiatives spanning multiple teams across the autonomous driving stack.
• Collaborate closely with teams working on: data, perception, simulation, safety validation, onboard systems.
• Define roadmaps and priorities aligned with product milestones and safety goals.
• Drive solutions from research prototypes through production deployment.

  Your Skills & Abilities

  • MS or PhD in Computer Science, Robotics, Machine Learning, or related field.
  • Experience leading technical teams delivering production ML systems.
  • Deep expertise in one or more areas: robotics planning and control, imitation learning or reinforcement learning, generative models, large-scale machine learning systems.
  • Strong software engineering skills (Python, C++, or similar).
  • Experience deploying ML models into real-world or safety-critical environments.
  • Demonstrated ability to define architecture and drive large technical initiatives across teams.

  Preferred Qualifications

  • Experience with autonomous driving, robotics, or embodied AI systems.
  • Background in trajectory planning, motion planning, or behavior modeling.
  • Experience with large-scale training infrastructure and distributed ML pipelines.
  • Experience with simulation-based training or evaluation of driving policies.

    About GM

    Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.

    Why Join Us

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    Benefits Overview

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