Director of Engineering, End to End Autonomous Driving

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA

NVIDIA is seeking a Director of Engineering to lead the design and deployment of end-to-end autonomous driving systems. This role focuses on leveraging LLMs, VLMs, and VLAs for advanced planning and reasoning in vehicles and robotics, involving strategic leadership, team management, and technical oversight of ML model development and integration into safety-critical production environments.

What you'd actually do

  1. Define the technical roadmap for large-scale generative, imitation, and reinforcement learning models to advance vehicle planning and reasoning.
  2. Recruit, mentor, and lead an extraordinary team of ML engineers passionate about building and fine-tuning LLM/VLM/VLA systems for real-world robotics.
  3. Oversee tactical execution of data generation and collection strategies to ensure the highest quality training datasets for production.
  4. Partner with hardware, firmware, and safety teams to deploy AI models in production environments, ensuring they meet rigorous performance and safety standards.
  5. Provide deep technical mentorship on integrating ML models into the rest of the autonomous driving stack to build production-quality, safety-critical software.

Skills

Required

  • Production Experience: Hands-on experience delivering pioneering ML planning models at scale in real-world environments.
  • Proven Leadership: 5+ years of experience managing high-performing ML teams with a focus on autonomous systems, robotics, or computer vision.
  • Technical Mastery: Deep understanding of modern deep learning architectures (LLMs, VLMs, or VLAs) and optimization techniques for large-scale training.
  • Product Delivery: A track record of shipping production-grade ML models at scale for safety-critical applications.
  • Strategic Vision: Ability to translate complex research into tactical engineering plans and long-term product roadmaps.
  • Master’s degree or PhD in CS, EE, or a related field (or equivalent experience).
  • 12+ overall years of professional experience in the AV or AI industry.

Nice to have

  • Experience scaling LLM/VLM/VLA systems specifically for embodied AI or real-time robotics.
  • Publications, open-source contributions, or competition wins related to LLM/VLM/VLA systems.
  • Success in managing multi-site teams and navigating the complexities of mass-production vehicle launches.
  • Deep expertise in behavior and motion planning within resource-constrained environments.
  • A strong track record of building large-scale data flywheels and training infrastructure and a background in optimizing high-performance algorithms for real-time deployment on NVIDIA hardware.

What the JD emphasized

  • Hands-on experience delivering pioneering ML planning models at scale in real-world environments.
  • A track record of shipping production-grade ML models at scale for safety-critical applications.

Other signals

  • leading the design and deployment of cutting-edge end-to-end autonomous systems
  • teaching an intelligent agent to drive
  • leveraging LLMs, VLMs, and VLAs to bring unprecedented reasoning and planning capabilities to autonomous vehicles and general robotics
  • define the technical roadmap for large-scale generative, imitation, and reinforcement learning models
  • shipping production-grade ML models at scale for safety-critical applications