Research Intern, World Models and Synthetic Data for Autonomous Driving - Summer 2027
Core
Develop generative world models and synthetic data engines to simulate complex driving environments and improve autonomous vehicle robustness.
Role type
Research Intern (Generative AI for Autonomous Driving)
Builds
Generative video/world models, controllable driving scenarios, and synthetic datasets for AV training.
Domain
Autonomous Driving / Generative AI / Computer Vision
Deliverable
research
Required skills
Deep learning, Generative modeling, Computer vision, Python, Neural network development, Experimental design
Preferred skills
Multimodal learning, 3D scene understanding, Diffusion models, Large-scale dataset curation, End-to-end learning
Technologies
PyTorch, TensorFlow, CUDA, Simulation frameworks (CARLA, LGSVL), Diffusion models, Transformers
Responsibilities
Research and prototype generative world models and traffic world models; Develop methods for controllable generation of safety-critical driving scenarios; Design and conduct experiments to evaluate how generated data affects AV model performance; Collaborate with researchers and engineers on research prototypes; Contribute to high-impact research publications.