NLP Algorithm Engineer - Search

1. Responsible for the exploration and implementation of search related algorithms, combining user portraits and personal knowledge graphs to improve the personalization and user understanding ability of AI applications 2. Based on the user's multimodal data, build the user's basic attributes, interest portraits and personal knowledge graphs 3. Responsible for the application of large models in vertical scenarios, and explore the implementation methods and effect improvement of large models.

1. Familiar with common machine learning and deep learning models, including classification, regression, clustering and other tasks. Priority will be given to those who have experience in large model principles and fine-tuning. 2. At least have relevant principles in one direction, such as search, NLP, knowledge graph, and graph, and understand the core and cutting-edge model algorithms in this direction. Priority will be given to those who have practical applications in search, NLP, and graph, including but not limited to intent recognition, query understanding, reference disambiguation, graph construction and application. 3. Familiar with C++/Java/Python, etc., and familiar with at least one mainstream deep learning framework (Tensorflow, Pytorch) 4. Priority will be given to those who have published papers as the first author in top conferences such as NLP and data mining (ACL, EMNLP, KDD, WWW, SIGIR, ICLR, NIPS, ICML, etc.).