Machine Learning Scientist, Biomolecular Structure Prediction

We're looking for a motivated and creative Machine Learning (ML) Scientist to drive research into biomolecular structure prediction. You will build and improve all-atom co-folding models, with a focus on the complexes that matter most to our programs: antibody–antigen interfaces and protein–nucleic acid assemblies. These remain among the hardest cases for current models, and closing that gap directly accelerates our antibody design and genome editing work.

The ideal candidate has trained structure prediction models at a leading academic or industry lab and knows where today's models break. You will be a self-directed researcher who moves quickly from hypothesis to trained model to rigorous evaluation. As an early member of the ML team, you will help shape how structure modeling fits alongside our generative models (ProGen3, E1) and experimental platforms.