Responsibilities
Team introduction: ByteDance search team is mainly responsible for search algorithm innovation and architecture research and development of Douyin, Toutiao, Xigua Video and other products. We use the most cutting-edge machine learning technology for end-to-end modeling and continue to innovate and make breakthroughs. At the same time, we focus on the construction and performance optimization of distributed systems and machine learning systems, from memory and disk optimization to the exploration of index compression, recall, sorting and other algorithms, fully providing students with opportunities to grow themselves. The main work directions include: 1) Exploring the most cutting-edge NLP technology: from basic word segmentation, NER, to application Query analysis, basic correlation, etc., applying deep learning models in the entire link, every detail is full of challenges 2) Exploring cross-modal matching technology: applying CV+NLP deep learning technology in search to give video search a more powerful retrieval capability 3) Explore large-scale streaming machine learning technology: apply large-scale machine learning to solve the recommendation problem in search, making the search more personalized and understand you better 4) Explore the architecture of hundreds of billions of data scale: from large-scale offline computing, distributed system performance and scheduling optimization to building high-availability, high-throughput and low-latency online services, conduct in-depth research and innovation in all aspects. 1. Participate in search engine research and development, explore personalized behavior modeling of the entire search link (analysis, recall, rough ranking, fine ranking, mixed ranking), including CTR, CVR estimation, vector recall, value mixing, RAG, NLP, LLM, multi-modal, machine learning, deep learning, etc., to promote the implementation and improvement of search algorithms 2. Participate in the development of search algorithms. Develop and iterate to improve conversion efficiency, user experience and supply ecology 3. In-depth participation in the demand design of search products, responsible for the high-quality delivery of algorithms and projects, and continuous optimization to improve product experience support the research and development of strategic algorithms for the entire search business such as tomato novels, red fruit short plays, soda music, etc., and improve the information distribution efficiency of each business from the search perspective 4. Mining data, building Query understanding, recall, sorting and other models to improve search algorithm capabilities 5. Learn cutting-edge technologies and explore the implementation of innovative technologies such as large models in AI search scenarios.
Qualifications
1. Bachelor degree or above in computer, electronics, mathematics and other related majors 2. Priority will be given to those who have in-depth researchers in one or more fields such as search, recommendation, search promotion, natural language processing NLP, natural language understanding NLU, multi-modal, machine learning, deep learning 3. Familiar with the Linux development environment, proficient in using C++ and Python languages 4. Have good problem analysis and solving skills, communication and collaboration skills, be proactive in work, and be able to work harmoniously with the team to explore new technologies and promote technological progress. Bonus points: 1. Those with excellent basic algorithms, solid machine learning/deep learning foundation, familiar with technologies in CV, NLP, RL, ML and other fields, priority will be given to those who have published papers in top conferences/journals such as ICML, ACL, COML, EMNLP, CVPR, ECCV, ICCV, NeurIPS, ICLR, SIGGRAPH or SIGGRAPH Asia 2. Applicants with excellent coding skills, proficient in C/C++ or Python programming language, winners of ACM/ICPC, NOI/IOl, Top Coder, Kaggle and other competitions are preferred 3. Applicants who have led projects with large impact in the fields of LLM, multimodality, large models, basic models, world models, RL, etc. are preferred 4. Applicants with relevant experience in large-scale search engines, recommendation systems, distributed systems, computational advertising, ultra-large-scale data calculations, etc. are preferred.
