Two core development tracks are available for candidates based on technical preferences (track alignment will be determined during interviews). Track 1: AI for Science 1.Cross border application of cutting edge technologies •Understand intersections between AI technologies and pharmaceutical industry. •Participate in or lead the development, optimization and deployment of research oriented algorithm models, and drive the adoption of AI in scientific computing and experimental workflows. 2.Interdisciplinary requirement engineering & technical translation •Collaborate closely with domain experts from research and industrial teams. Translate core scientific challenges into computable machine learning tasks. •Build and maintain scientific datasets, and advance data standardization and data asset management. 3.Cutting edge technology tracking & innovation ecosystem building •Keep track of global academic advances in the AI for Science field. Deliver technical research reports and commercial feasibility analyses. Track 2: AI for Productivity 1.Build end to end intelligent Agents •Design and develop production ready intelligent Agents and application workflows based on large language models, RAG, enterprise knowledge bases and business rules, targeting corporate workflows, business processes and cross border collaboration scenarios. 2.Overseas oriented AI & global scale applications •Identify high value AI opportunities within operations, knowledge management and office collaboration for international business teams. Construct multilingual knowledge bases and localized AI solutions. 3.Data science project delivery (Machine Learning) •Participate in full cycle machine learning projects driven by real world business problems. Translate business objectives into verifiable data science tasks, and contribute to data exploration, cleansing, feature engineering and sample dataset construction. 4.PMO & project management •Support end to end governance of key digital projects to facilitate cross team alignment and on time delivery. 5.Foundry attribution and reasoning platform development •Leverage the Foundry platform to build data association capabilities for complex enterprise decision making. Design Ontology business objects, data lineage and reasoning pipelines to enable cross domain data linkage and sophisticated attribution analysis.

1.Educational Background •Bachelor’s degree or above. Graduates from top tier Chinese universities or well known overseas institutions are preferred. Majors: Computer Science, Artificial Intelligence, Software Engineering, Data Science, Bioinformatics, Electronic Information, Mathematics, Statistics or related disciplines. 2.Specialized competency requirements by track (meeting any one of the following is sufficient) 【For AI for Science candidates】: •Solid foundation in algorithms and data science, with proficiency in at least one of the following: machine learning, deep learning, NLP or bioinformatics algorithms. •Proficient in Python; familiar with SQL, Pandas and mainstream data analysis & modeling toolkits. •Hands on experience in AI / algorithm focused research, competitions or academic projects during university; relevant research or internship experience in medicine, clinical trials or biopharmaceuticals is a plus. 【For AI for Productivity candidates】: •Proficient in Python; familiar with software development workflows and LLM based application development (Prompt engineering, RAG, Agent workflows, tool calling, etc.). •Hands on experience with AI augmented development tools such as Cursor, Claude Code and GitHub Copilot to improve R&D efficiency. •Skilled with SQL, Pandas and other data processing libraries for data cleansing, relational analysis, anomaly detection and data visualization. 3.Soft Skills & Competencies •Strong interest in digital transformation of the pharmaceutical industry, AI enabled business empowerment and real world deployment of advanced technologies. •Excellent structured thinking and business problem decomposition skills, capable of translating complex business and office requirements into clear product oriented tasks. •Sharp logical reasoning, fast learning agility, self motivation and strong teamwork orientation. •Solid English proficiency in reading, writing, listening and speaking to support cross regional and cross cultural collaboration.