26届精英计划-数字化支持-26届 (MJ007741)

This position is for WuXi Vaccines.(苏州药明海德） Role De scription We are seeking a passionate AI Engineer to serve as a key member of our interdisciplinary team, designing, building, and deploying AI/ML platforms and solutions for Vaccine process development, manufacturing site. You will be responsible for transitioning algorithmic prototypes into robust, scalable, production-grade systems, handling multimodal biomedical data (chemical, biological, imaging, textual), and collaborating closely with scientists, biologists, and chemists. Key Responsibilities 1. AI Model Engineering & Deployment: · Collaborate with data scientists to refactor, optimize, and deploy experimental machine learning models (e.g., for molecular property prediction, target identification, clinical trial optimization) into production environments. · Develop and maintain robust MLOps pipelines encompassing model training, validation, monitoring, versioning, and automated retraining. · Build high-performance data processing and feature engineering pipelines to handle large-scale structured and unstructured data. 2. AI Platform & Tool Development: · Contribute to the construction and maintenance of the company's internal AI/ML platform, providing self-service model development and data analysis tools for research scientists. · Develop software libraries and APIs for cheminformatics and bioinformatics analysis. · Integrate and manage third-party scientific software, databases, and cloud resources (AWS/Azure/GCP, particularly biomedical cloud services). 3. Cross-Functional Collaboration & Solution Delivery: · Deeply understand pain points in the drug R&D pipeline (e.g., target identification, compound screening, ADMET prediction, preclinical studies) and translate them into well-defined technical problems. · Communicate effectively with wet-lab scientists, interpret model results, and iteratively refine models based on biological feedback. · Ensure all developed tools and systems comply with R&D department regulations and data security requirements. Key Qualifications: 1. Master’s degree or higher with chemoinformatics, bioinformatics, or computational biology, Data Science, Engineering or related fields. 2. Familiarity with the application of generative models (VAE, GAN, Diffusion, LLM) in molecule generation, retrosynthesis, or scientific literature mining. 3. Knowledge of and compliance with relevant pharmaceutical industry regulations (e.g., GxP, 21 CFR Part 11, FAIR data principles) and IT compliance requirements.