Machine Learning Intern, Perception (End-to-end)
Core
Researching end-to-end autonomous driving models connecting perception, reasoning, prediction, and action using learning-based approaches.
Role type
Research Intern (End-to-end Autonomous Driving)
Builds
Learning-based models for perception, scene understanding, future prediction, and driving action generation
Domain
Autonomous driving, Robotics, AI
Deliverable
research
Required skills
Python, C++, PyTorch, TensorFlow, computer vision, sequence modeling, imitation learning, reinforcement learning, robotics, planning, autonomous driving, model training, evaluation, ablation studies, structured/unstructured data handling
Preferred skills
end-to-end autonomous driving, Vision-Action models, Vision-Language-Action models, world models, large-scale model training, distributed training, autonomous driving datasets (nuScenes, Waymo, Argoverse, NAVSIM, CARLA), publications, open-source contributions
Technologies
PyTorch, TensorFlow, nuScenes, Waymo Open Dataset, Argoverse, NAVSIM, CARLA