- Shanghai, China
- Internship · Intern
The role involves researching, prototyping, and implementing state-of-the-art Reinforcement Learning (RL) algorithms for autonomous vehicle decision-making and trajectory planning.
Responsibilities
- Research, prototype, and implement state-of-the-art Reinforcement Learning (RL) algorithms for autonomous vehicle decision-making and trajectory planning.
- Assist in developing and scaling training pipelines and simulation environments for complex RL experiments.
- Collaborate closely with senior researchers and engineers across perception and planning teams to integrate RL models into the autonomous driving stack.
- Analyze and benchmark RL model performance against imitation learning and traditional baselines in complex urban simulation scenarios.
- Explore techniques to optimize and lightweight RL policies for real-time deployment on automotive hardware.
Requirements
- MS or PhD in Computer Science
- Robotics
- Electrical Engineering
- related quantitative field
- Nice to have: Publication record at top-tier AI/Robotics conferences (NeurIPS, ICML, IROS, ICRA, CoRL)