Responsibilities
1. Responsible for the construction of industry AI search capabilities, including but not limited to games, e-commerce, business consulting, videos, pictures, articles, etc., to provide users with intelligent, accurate and rich search experience 2. From search scenarios of different scales from tens of thousands to hundreds of billions, apply LLM technology and other NLP and multimodal machine learning technologies to build AI retrieval products, including but not limited to RAG, semantic retrieval, image search, audio and video search, etc. 3. Construction of the full-stack search (query analysis, relevance, recall, rough ranking, fine ranking, mixed ranking), including relevance calculation, CTR estimation, CVR estimation, vector recall, value mixed ranking, etc. 4. Construction of AI retrieval capabilities, exploration of the most cutting-edge NLP technology and multimodal technology, from basic word segmentation, NER, OCR to application-based query analysis, basic relevance, etc., full-link application of deep learning models 5. Work closely with team members to transform research results into practical applications and promote product innovation and upgrades.
Qualifications
1. Excellent coding skills, data structure and basic algorithm skills, proficient in Java or Python, ACM/ICPC, NOI/IOI, Top Coder, Kaggle and other competition winners are preferred 2. Excellent problem analysis and problem solving skills, pursuit of elegant architecture design and code quality, and passion for challenging technical problems 3. Familiar with the basic theory of information retrieval, and those with experience in mainstream recommendation/search engine architecture development are preferred 4. Familiar with the application and optimization of machine learning models in the search link, and those with experience in intelligent search architecture development are preferred 5. Good communication and collaboration skills, able to explore new technologies with the team and promote technological progress.
