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

at Nvidia

📍 Santa Clara, United States

USD 184,000-356,500 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 @ 6 Deep Learning @ 7 LLM @ 4 Machine Learning @ 4 Python @ 7 Reinforcement Learning Robotics @ 4

Details

NVIDIA is seeking exceptional engineers to join its autonomous driving team and design, implement, and deploy end-to-end autonomous driving systems running on NVIDIA chips in mass-production vehicles. The team is advancing from AI 1.0, building a driver from scratch, to AI 2.0, teaching an intelligent agent to drive using LLMs, VLMs, and VLAs for enhanced reasoning, planning, and interactivity in 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 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 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 passionate about autonomous systems.
Deep understanding of modern deep learning architectures and optimization techniques.
Proven experience 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.
PhD with 4 or more years of experience, or an MS degree or equivalent experience with 6 or more years of relevant experience, in Computer Science, Computer Engineering, or a related technical 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.
Ability to optimize algorithms for real-time performance in resource-constrained environments.
Strong track record of taking projects from concept through production deployment.

Compensation and Benefits

Level 4 base salary: USD 184,000–287,500 per year.
Level 5 base salary: USD 224,000–356,500 per year.
Compensation is determined based on location, experience, and the pay of employees in similar positions.
Eligible employees also receive equity and benefits.
Applications will be accepted at least until March 26, 2026.
NVIDIA is an equal opportunity employer committed to fostering a diverse work environment.
NVIDIA uses AI tools in its recruiting processes.