As a Senior Scientist in Machine Learning, you will design, develop, and evaluate state-of-the-art foundation models at scale, including pre-training and fine-tuning large-scale systems with multimodal biological data, natural language, and structured inputs. You will architect hybrid models integrating Large Language Models (LLMs) with Graph Neural Networks (GNNs) for multi-hop reasoning over biological knowledge graphs, and develop Relational Foundation Models (RFMs) for zero-shot predictive tasks.… You will lead the design of efficient distributed training strategies across multiple GPU nodes, mentor junior staff, and transition research prototypes into production systems. The role requires a PhD in Computer Science or Machine Learning with 5+ years of experience, strong Python and deep learning library expertise, proven multi-GPU distributed training experience, and a track record of peer-reviewed AI/ML research publications.