Research Intern, World Models and Synthetic Data for Autonomous Driving – Summer 2027

Details

Be part of the Autonomous Vehicle (AV) Applied Research team and help advance safe autonomy through generative world models and synthetic data. This internship involves working with researchers and engineers to develop models that understand, simulate, and reason about complex driving environments.

The team focuses on generative video and world models, controllable scenario generation, multimodal learning, end-to-end driving, 3D computer vision, and data-centric learning. The research uses generative models to create diverse, safety-critical, and long-tail driving experiences that improve the robustness and generalization of autonomous systems.

Responsibilities

• Research and prototype generative world models, traffic world models, and synthetic-data generation methods for autonomous driving.
• Develop traffic world models that capture multi-agent interactions and realistic, reactive behaviors for simulating and generating complex driving scenarios.
• Develop methods for controllable generation of diverse, interactive, and safety-critical driving scenarios.
• Explore generative video models, multimodal foundation models, traffic simulation, data curation, active learning, self-supervised learning, and simulation to improve training-data quality, diversity, and coverage.
• Design and conduct experiments to evaluate how generated data affects autonomous vehicle model performance, robustness, and generalization.
• Translate advances in generative modeling and machine learning into practical approaches for autonomous driving.
• Collaborate with researchers and engineers across NVIDIA on research prototypes and experimental systems.
• Contribute to research publications and open research efforts.

Requirements

• Currently pursuing a Ph.D. or M.S. in Computer Science, Electrical or Computer Engineering, Robotics, or a related field.
• Research experience in deep learning, computer vision, generative modeling, multimodal learning, robotics, or autonomous driving.
• Strong foundations in machine learning and deep learning, with hands-on experience developing and evaluating neural-network models.
• Experience in one or more of generative models, video generation, multimodal learning, 3D computer vision, autonomous driving, or robotics.
• Strong mathematical and analytical skills, with an interest in designing rigorous experiments.
• Strong Python programming skills and experience with modern deep learning frameworks.
• Self-motivated, collaborative, and comfortable working in a research environment with open-ended problems.

Preferred Qualifications

• Publications or research projects at venues such as NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, or related conferences.
• Hands-on experience with generative world models, video generation, diffusion models, autoregressive models, multimodal foundation models, or synthetic-data generation.
• Experience working with large-scale video, driving, robotics, or simulation datasets.
• Experience with autonomous driving, embodied AI, physical AI, 3D scene understanding, or end-to-end learning.
• Demonstrated ability to take a research idea from hypothesis through implementation, experimentation, and quantitative evaluation.

Benefits

NVIDIA offers competitive compensation and a comprehensive benefits package. Interns are eligible for intern benefits. Applications will be accepted at least until October 13, 2026. NVIDIA is committed to an inclusive work environment and is an equal opportunity employer.