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

at Nvidia

📍 Santa Clara, United States

USD 272,000-431,200 per year

SENIOR

✅ On-site

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI Algorithms @ 7 Deep Learning @ 7 LLM @ 4 Machine Learning @ 6 Python @ 7 Reinforcement Learning Robotics @ 4

Details

At NVIDIA, we are seeking exceptional engineers to join our autonomous driving team to design, implement, and deploy cutting-edge end-to-end autonomous driving systems running on NVIDIA chips in mass-production vehicles. Our strategy has evolved from AI 1.0—building a driver from scratch—to AI 2.0—teaching an intelligent agent to drive. This next phase leverages LLMs, VLMs, and VLAs to bring unprecedented reasoning, planning capabilities, and interactivity to autonomous vehicles and general robotics.

Responsibilities

Design and train innovative large-scale models, including generative, imitation, and reinforcement learning models, to improve the planning and reasoning capabilities of driving systems.
Build, pre-train, and fine-tune LLM, VLM, and VLA systems for deployment in real-world autonomous driving and robotics applications.
Explore novel data generation and collection strategies to improve the diversity and quality of training datasets.
Collaborate with cross-functional teams to deploy AI models in production environments, ensuring performance, safety, and reliability standards are met.
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 passionate about autonomous systems.
Deep understanding of modern deep learning architectures and optimization techniques.
Proven record of deploying production-grade machine learning models for self-driving, robotics, or related fields at scale.
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 equivalent experience with 13+ years of work experience in autonomous vehicles or a related field, or a PhD with 11 years of work experience in autonomous vehicles or a related field.

Preferred Qualifications

Experience with LLM, VLM, or VLA systems deployable to autonomous vehicles or general robotics.
Publications, open-source contributions, or competition wins related to LLM, VLM, or VLA systems.
Deep understanding of behavior and motion planning in real-world autonomous vehicle 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 and Benefits

The base salary range is USD 272,000–431,250. Base salary will be determined based on location, experience, and the pay of employees in similar positions. The role also includes eligibility for equity and benefits.

NVIDIA is committed to fostering a diverse work environment and is an equal opportunity employer. NVIDIA uses AI tools in its recruiting processes.