NVIDIA 2027 Internships: Ph.D. Research Autonomous Vehicles

By submitting your resume, you acknowledge that your Ph . D .   Research   Autonomous Vehicles internship application will be processed in accordance with NVIDIA’s Applicant Privacy Policy and you agree to our Terms of Service . We’ll 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.   We’re   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 .

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 Ph.D. degree in Computer Science, Electrical Engineering, or a related field, for the full duration of the internship;   anticipated graduation date ( month and year )   must be clearly indicated on a resume or CV to be considered.   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   i nternships 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   here   to 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 38 USD - 94 USD.
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