
Learning-based Planning and Prediction Research Scientist for Autonomous Driving_CR
- Shanghai
- Permanent
- Full-time
- Research and develop scalable planning and prediction systems based on machine learning to generate safe and feasible trajectories for autonomous driving, covering aspects such as code implementation, model training, parameter tuning, and iterative optimization.
- Collaborate closely with the perception R&D team to ensure that the developed algorithms efficiently and safely support advanced intelligent driving functions.
- Stay up-to-date with cutting-edge machine learning technologies, explore their feasibility in autonomous driving prediction and planning, propose and implement practical solutions, and deploy them in real-world vehicles.
- Have a comprehensive understanding of machine learning algorithms, with the ability to quickly adapt to and drive the development of new technologies.
- Master's degree or above in Computer Science, Automation, Robotics, Artificial Intelligence, or a related field, with a strong foundation in mathematics and algorithms. Experience in autonomous driving R&D is preferred.
- Familiar with current mainstream machine learning algorithms and proficient in one or more areas of algorithm research, including but not limited to CNN, transformer, diffusion, GNN, and reinforcement learning.
- Strong programming skills, proficient in C++ and Python languages, as well as PyTorch or TensorFlow frameworks. A solid foundation in data structures and algorithms; experience in ACM competitions is preferred.
- Passionate about the autonomous driving industry, with excellent communication skills and a strong sense of teamwork.
- Familiarity with traditional motion trajectory planning algorithms is a plus, such as A*, lattice planner, RRT, etc.
- Preference will be given to candidates who have published research papers at top conferences such as NeurIPS, ICLR, ICML, CVPR, RSS, CoRL, etc.