NVIDIA
NVIDIA 2026 Internships: PhD Autonomous Vehicles Research - US
NVIDIA, Santa Clara, California, us, 95053
By submitting your resume, youre expressing interest in one of our 2026 Autonomous Vehicles focused Research Internships. Well review resumes on an ongoing basis, and a recruiter may reach out if your experience fits one of our many internship opportunities.
NVIDIA pioneered accelerated computing to tackle challenges no one else can solve. Our work in AI and digital twins is transforming the world's largest industries and profoundly impacting society from gaming to robotics, self-driving cars to life-saving healthcare, climate change to virtual worlds where we can all connect and create.
Our internships offer an excellent opportunity to expand your career and get hands on experience with one of our industry leading Autonomous Vehicles teams. Were seeking strategic, ambitious, hard-working, and creative individuals who are passionate about helping us tackle challenges no one else can solve.
Learn more about Research at NVIDIA.
What you will be doing:
Design and implement cutting-edge techniques in the field of vehicle autonomy.
Collaborate with other team members, teams, and/or external researchers.
Transfer your research to product groups to enable new products or types of products. Deliverable results include prototypes, patents, products, and/or publishing original research.
What we need to see: Must be actively enrolled in a university pursuing a PhD degree in Computer Science, Electrical Engineering, or a related field, for the entire duration of the internship.
Depending on the internship, prior experience or knowledge requirements could
include the following programming skills and technologies:
Python, C++, CUDA, Deep Learning Frameworks (PyTorch, TensorFlow, etc.)
Strong background in research with publications at top conferences.
Excellent communication and collaboration skills.
Experience with large-scale model training is a plus.
Potential internships require research experience in at least one of the following areas: Next-Generation AV Architectures Chain-of-Thought Reasoning
Mixture-of-Experts
Diffusion-LLMs
Diffusion-based Trajectory Decoding
Novel Policy Training Strategies Closed-loop Training
Off-policy RL
Online RL
Enforcing Consistency
Foundation and Multimodal Models Vision-language models
Multimodal reasoning
Spatial Multimodal Models
Modality Alignment
Model Scaling
Synthetic data
Inference Efficiency Inference Optimizations (e.g., parallel decoding, speculative decoding)
Token Representations
Model Distillation
Simulation and Behavior Modeling Digital Twins
Scenario Generation
World Models
Behavior/Traffic Modeling
End-to-End AV Systems Mapless driving
World Representations
Beyond imitation learning
Safety-aware end-to-end models
Perception and Representation Learning Multi-modal sensor fusion
2D/3D detection, segmentation, depth estimation, scene understanding, neural representations
Safe and Trustworthy Autonomous Systems Principled robustness
Model explainability
Control Barrier Functions (CBFs)
Verification and Validation of Safety-Critical AI Systems
Trustworthy AI/ML for autonomy and robotics
Data-Strategies for AI Benchmarking AV Click hereto learn more about NVIDIA, our early talent programs, benefits offered to students and other helpful student resources related to our latest technologies and endeavors. 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 30 USD - 94 USD. You will also be eligible for Intern benefits. ? Applications are accepted on an ongoing basis.
NVIDIA is committed to fostering a diverse 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.
Collaborate with other team members, teams, and/or external researchers.
Transfer your research to product groups to enable new products or types of products. Deliverable results include prototypes, patents, products, and/or publishing original research.
What we need to see: Must be actively enrolled in a university pursuing a PhD degree in Computer Science, Electrical Engineering, or a related field, for the entire duration of the internship.
Depending on the internship, prior experience or knowledge requirements could
include the following programming skills and technologies:
Python, C++, CUDA, Deep Learning Frameworks (PyTorch, TensorFlow, etc.)
Strong background in research with publications at top conferences.
Excellent communication and collaboration skills.
Experience with large-scale model training is a plus.
Potential internships require research experience in at least one of the following areas: Next-Generation AV Architectures Chain-of-Thought Reasoning
Mixture-of-Experts
Diffusion-LLMs
Diffusion-based Trajectory Decoding
Novel Policy Training Strategies Closed-loop Training
Off-policy RL
Online RL
Enforcing Consistency
Foundation and Multimodal Models Vision-language models
Multimodal reasoning
Spatial Multimodal Models
Modality Alignment
Model Scaling
Synthetic data
Inference Efficiency Inference Optimizations (e.g., parallel decoding, speculative decoding)
Token Representations
Model Distillation
Simulation and Behavior Modeling Digital Twins
Scenario Generation
World Models
Behavior/Traffic Modeling
End-to-End AV Systems Mapless driving
World Representations
Beyond imitation learning
Safety-aware end-to-end models
Perception and Representation Learning Multi-modal sensor fusion
2D/3D detection, segmentation, depth estimation, scene understanding, neural representations
Safe and Trustworthy Autonomous Systems Principled robustness
Model explainability
Control Barrier Functions (CBFs)
Verification and Validation of Safety-Critical AI Systems
Trustworthy AI/ML for autonomy and robotics
Data-Strategies for AI Benchmarking AV Click hereto learn more about NVIDIA, our early talent programs, benefits offered to students and other helpful student resources related to our latest technologies and endeavors. 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 30 USD - 94 USD. You will also be eligible for Intern benefits. ? Applications are accepted on an ongoing basis.
NVIDIA is committed to fostering a diverse 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.