We are recruiting outstanding Research Interns to work on autonomous vehicles, robotics, and physical AI! Intelligent machines that can perceive, reason, and safely interact with people and the physical world are rapidly becoming a reality. Self-driving cars, autonomous delivery and construction vehicles, mobile manipulators, and other robotic systems are moving closer to widespread deployment. However, fundamental research challenges remain before these systems can operate safely, reliably, and autonomously in complex, unfamiliar environments.
For example, how can we:
Develop new training paradigms that use perception and interaction to train autonomous vehicle and robot policies in closed loop?
Equip autonomous systems with online and offline assurances that meet the requirements of safety-critical applications?
Enable vehicles and robots to navigate across new environments, tasks, and embodiments?
Build systems that reason under uncertainty and interact safely and naturally with people and other agents?
These are some of the exciting questions being explored by NVIDIA’s Autonomous Systems and Physical AI Research (ASPIRE) group. Our diverse, interdisciplinary team conducts foundational research spanning foundation model design, embodied reasoning, safety, closed-loop training and evaluation, and agentic workflows for Physical AI development. We also investigate related areas including decision-making under uncertainty, deep learning, reinforcement learning, simulation, and the verification and validation of safety-critical AI systems. Our focus is on fundamental research, and lab members are encouraged to publish their work and open-source their code. NVIDIA is known for its collaborative culture, and our researchers work closely with experts across the company in autonomous vehicles, robotics, perception, simulation, and machine learning. This creates opportunities to influence real-world products while retaining the freedom and bandwidth to conduct groundbreaking, publishable research.
What you’ll be doing:
Designing and implementing cutting-edge techniques for autonomous vehicles, robotics, and physical AI.
Conducting original research and publishing your results.
Collaborating with research colleagues, internal product teams, and external researchers.
Transferring technology you’ve developed to relevant product groups.
What we need to see:
Currently pursuing a PhD in Robotics, Computer Science, Computer Engineering, or a related field.
Relevant research experience in autonomous vehicles, robotics, embodied AI, or autonomous systems.
Strong knowledge of the theory and practice of vehicle or robot autonomy—or expertise in a related area, with a strong interest in applying your work to autonomous systems.
A track record of research excellence, demonstrated through publications at leading conferences and journals—such as RSS, ICRA, CoRL, IJRR, NeurIPS, ICML, CVPR, TAC, etc.—and through other research artifacts such as open-source software.
Exceptional Python programming skills; experience with C++ and parallel programming, such as CUDA, is a plus.
Experience with machine learning frameworks such as PyTorch.
Strong communication and interpersonal skills are required, along with the ability to thrive in a dynamic, research-focused team.
Are you intellectually curious, collaborative, and motivated to solve complex problems at the intersection of AI and the physical world? If so, you may be a great fit for NVIDIA.
Our internship hourly rates are a standard pay based on the position, your location, year in school, degree, and experience. The hourly rate for our interns is 38 USD - 94 USD.
You will also be eligible for Intern benefits.
Applications for this job will be accepted at least until October 16, 2026.
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.