Deep Learning Engineer, End-to-End Autonomous Driving

at Nvidia
USD 184,000-356,500 per year
MIDDLE
βœ… On-site

SCRAPED

Used Tools & Technologies

Not specified

Required Skills & Competences ?

Python @ 6 Algorithms @ 6 Machine Learning @ 3 Planning @ 3 LLM @ 3

Details

We are building the next generation of end-to-end autonomous driving systems that run on NVIDIA hardware. The team is moving from designing drivers from scratch toward AI-driven agents that leverage LLMs, VLMs, and VLAs to provide advanced reasoning, planning, and interactivity for autonomous vehicles and robotics.

Responsibilities

  • Design and train large-scale models, including generative, imitation, and reinforcement learning approaches to improve planning and reasoning for driving systems.
  • Build, pre-train, and fine-tune LLM, VLM, and VLA systems for real-world autonomous driving and robotics deployments.
  • Explore and develop novel data generation and collection strategies to increase diversity and quality of training datasets.
  • Collaborate with cross-functional teams to deploy AI models into production environments while meeting performance, safety, and reliability standards.
  • Integrate machine learning models directly with vehicle firmware to deliver production-quality, safety-critical software.

Requirements

  • Hands-on experience building LLMs, VLMs, or VLAs from scratch OR a proven track record as a top-tier coder with a passion for autonomous systems.
  • Deep understanding of modern deep learning architectures and optimization techniques.
  • Proven experience deploying production-grade ML models at scale in self-driving, robotics, or closely related domains.
  • Strong programming skills in Python and proficiency with major deep learning frameworks.
  • Familiarity with C++ for model deployment and integration in safety-critical systems.
  • Master's degree or PhD (or equivalent experience).
  • 8+ years of work experience in autonomous vehicles (AV) or a related field.

Ways to Stand Out

  • Experience with LLM/VLM/VLA systems that are deployable to autonomous vehicles or general robotics.
  • Publications, open-source contributions, or competition wins related to LLM/VLM/VLA systems.
  • Deep understanding of behavior and motion planning in real-world AV applications.
  • Experience building and training large-scale datasets and models.
  • Proven ability to optimize algorithms for real-time performance in resource-constrained environments and a strong track record of taking projects from concept to production deployment.

Compensation & Benefits

  • Base salary range:
    • Level 4: 184,000 USD - 287,500 USD
    • Level 5: 224,000 USD - 356,500 USD
  • Eligible for equity and additional company benefits. (Link to NVIDIA benefits provided in original posting.)

Location & Application Deadline

  • Location: Santa Clara, CA, United States (on-site role by location listing).
  • Applications accepted at least until August 23, 2025.

Equal Opportunity

  • NVIDIA is an equal opportunity employer and is committed to fostering a diverse work environment. The company does not discriminate based on protected characteristics.

#deeplearning