1. Proficient in the network structure and training methods related to large language models and multi-modal large models；

2. Proficient in Pytorch/Tensorflow deep learning framework, master at least one programming language Python/C++；

3. Proficient in common distributed training frameworks and efficient fine-tuning techniques for large models；

4. Proficient in using cloud computing power to carry out large-scale data processing and training；

5. Proficient in common imitation learning algorithms (such as ACT, DP, etc.) and Model-based RL algorithms are preferred；

6. Proficient in model and robot hardware interface layout is preferred；

7. Those who have published papers in AI, CV, NLP top conferences, and top journals (such as TIP, TRO, CVPR, ACL, etc.) are preferred.