We are now seeking a Sr Research Scientist for Autonomous Vehicles!
NVIDIA is recruiting top Senior Research Scientists for Autonomous Vehicle Research! AI-powered autonomous vehicles that can learn, reason, and interact with people are no longer science fiction. Self-driving cars, autonomous delivery vehicles, and autonomous construction vehicles, among others, are getting increasingly close to widespread deployment. However, fundamental research questions still need to be addressed for us to achieve full vehicle autonomy. For instance, how can we: Enable novel training paradigms that leverage simulation to train AV policies in closed-loop? Equip autonomous vehicles with online and offline assurances that meet the standards for safety-critical systems? Ensure that autonomous vehicles work seamlessly in new places?
These are some of the exciting questions that the NVIDIA Autonomous Vehicle Research group is tackling. We bring together a diverse, interdisciplinary research team working on core topics in vehicle autonomy, including agent behavior models, end-to-end AV architectures, AI safety, closed-loop training approaches, and AV foundation models (VLMs, reasoning models, etc.). Our focus is on basic and applied research; lab members are encouraged to publish their work and open-source code as well as provide real-world impact by deploying technology within production systems. NVIDIA is well known for its team culture, and lab researchers are able to closely interact with others within the company who are experts in perception systems, machine learning, and robotics. There is an opportunity to make a strong impact on products, while having the freedom and bandwidth to conduct ground-breaking publishable research.
What you'll be doing:
Designing and implementing cutting-edge techniques in the field of vehicle autonomy.
Publish and present your original research, speak at conferences and events.
Collaborate with other research team members, a diverse set of internal product teams, and external researchers.
Have a broader impact through the transfer and/or open-source of the technology you've developed to relevant product groups.
Collaborate closely with product teams to transfer research results into high-end, production-level systems.
What we need to see:
Ph.D. in Computer Science/Engineering, Electrical Engineering, or a related field (or equivalent experience).
6+ years of relevant research experience in the field of vehicle / robot autonomy.
Strong knowledge of theory and practice of vehicle / robot autonomy, or a related area with a strong interest in connecting your work to autonomous vehicles.
A track record of research excellence with your work published in top conferences and journals such as RSS, ICRA, IJRR, NeurIPS, ICML, CVPR, TAC, etc, and other research artifacts such as software projects
Excellent collaboration and interpersonal skills
Exceptional programming skills in Python; C++ and parallel programming (e.g., CUDA).
Solid understanding of common machine learning frameworks such as PyTorch and Tensorflow.
Strong communication and interpersonal skills are required along with the ability to work in a dynamic, research-focused team.
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. Are you a creative and autonomous research scientist with a genuine passion for advancing the state of AI? If so, we want to hear from you!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 192,000 USD - 304,750 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.Skills Required
- Ph.D. in Computer Science/Engineering, Electrical Engineering, or related field (or equivalent experience).
- 6+ years of relevant research experience in vehicle/robot autonomy.
- Strong knowledge of theory and practice of vehicle/robot autonomy or closely related area with interest in AVs.
- Track record of research excellence with publications in top conferences and journals (RSS, ICRA, IJRR, NeurIPS, ICML, CVPR, TAC, etc.) and/or significant research artifacts.
- Exceptional programming skills in Python; strong C++ and parallel programming experience (e.g., CUDA).
- Solid understanding and practical experience with machine learning frameworks such as PyTorch and TensorFlow.
- Excellent collaboration, communication, and interpersonal skills; ability to work in dynamic, research-focused teams.
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
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