Deep Learning Senior Engineer, End-to-end Autonomous Driving

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA +1 · Remote

NVIDIA is looking for a Deep Learning Senior Engineer to design, implement, and deploy end-to-end autonomous driving systems. The role focuses on leveraging LLMs, VLMs, and VLAs for reasoning and planning, involving model training, pre-training, fine-tuning, and integration into safety-critical vehicle firmware. Experience with production-grade ML models and C++ for deployment is required.

What you'd actually do

  1. Design and train innovative large-scale models—including generative, imitation, and reinforcement learning—to improve the planning and reasoning capabilities of our driving systems.
  2. Build, pre-train, and fine-tune LLM/VLM/VLA systems for deployment in real-world autonomous driving and robotics applications.
  3. Explore novel data generation and collection strategies to improve diversity and quality of training datasets.
  4. Collaborate with cross-functional teams to deploy AI models in production environments, ensuring performance, safety, and reliability standards are met.
  5. Integrate machine learning models directly with vehicle firmware to deliver production-quality, safety-critical software.

Skills

Required

  • Python
  • C++
  • deep learning frameworks
  • deep learning architectures
  • optimization techniques
  • LLMs
  • VLMs
  • VLAs

Nice to have

  • autonomous vehicles
  • robotics
  • LLM/VLM/VLA systems deployable to autonomous vehicles or general robotics
  • behavior and motion planning
  • large-scale datasets
  • real-time performance optimization
  • resource-constrained environments
  • concept to production deployment
  • publications
  • open-source contributions
  • competition wins

What the JD emphasized

  • deploy production-grade ML models
  • production deployment
  • safety-critical

Other signals

  • LLMs
  • VLMs
  • VLAs
  • autonomous driving
  • robotics
  • end-to-end systems
  • production deployment