enhance and accelerate portfolio decision-making. Задачи: Bring ML engineering expertise into architectural design, ensuring foundation models are efficient and scalable; Implement biomedical foundation model components, including training code, data loaders, tokenisers, inference logic and fine‐tuning interfaces; Translate validated research prototypes into robust, production-quality model artefacts … pruning to meet production efficiency and latency requirements; Write clean, well‐tested and well‐documented code and uphold engineering standards across the team; Lead model handovers to MLOps engineers with documentation covering capabilities, known limitations, failure modes and retraining criteria; Stay current with advances in ML engineering, distributed training ...