AI Scientist (Model Building & Training)

Role: AI Scientist specializing in drug discovery, focusing on designing, training, and evaluating foundation models to advance molecular and biological understanding. Responsibilities: develop generative and predictive AI models for chemistry and biology; translate machine learning into scientific insights for molecular design, target ID, genomics, and structure-based discovery; establish evaluation metrics connecting model performance to experimental outcomes; collaborate closely with multidisciplinary research teams to accelerate AI-driven discovery. Requirements: PhD in Machine Learning, Computational Chemistry, Biology, or related field; 2+ years post-PhD research experience; expertise in ML frameworks like PyTorch or JAX; proven contributions in scientific publications, patents, or open-source; experience working with scientific datasets and large neural networks on GPU infrastructure. Preferred: strong publication record, impact-driven research, and cross-disciplinary communication skills. HighValue: focus on foundational AI models applied to chemical and biological systems, particularly in early-stage drug discovery pursuits. WorkSetup: hybrid at Silicon Valley location; collaboration with Lilly scientists, NVIDIA engineers, and cross-functional teams.