1. Responsible for the research and implementation of LLM-related underlying technologies, and break through GPT-related generative large models. 2. Combine the pre-trained model with practical problems in multiple fields such as text classification, semantic search, NER, and dialogue, and comprehensively improve the R&D tasks and innovative applications of search and NLP.

1. Solid programming foundation, proficient in python, etc.; 2. Familiar with the principles and algorithms of deep learning and common machine learning algorithms, and be able to skillfully use clustering, classification, regression, sorting and other models to solve challenging problems; 3. Familiar with text semantic matching, machine reading comprehension, sorting model, recommendation system, etc. 4. Experience in the development of pre-trained models, in-depth understanding of Bert and GPT-related principles, such as prompt, finetuning, transformer and other key technologies, and be able to solve the problem of intent understanding; 5. Have a strong desire for knowledge and enthusiasm for related technologies in the field of artificial intelligence; 6. Have a good foundation in mathematics, good English reading skills and good team spirit. The following experience is preferred: 1. Ph.D. is preferred, and Class A papers such as ACL/AAAI/KDD/NIPS/CVPR are preferred; 2. Experience in GPT generative model development is preferred;