Senior ML Scientist

Ten63 Therapeutics develops computationally designed therapeutics for cancer and other lethal diseases using its BEYOND in silico platform, which combines quantum simulations and generative chemistry. The Senior ML Scientist will develop and lead deep learning models for computational chemistry and drug discovery, integrate physics-based simulations with learned models, and collaborate with AI engineers, chemists, and drug designers to advance models from research into production.

Responsibilities:

• Design, implement, and train deep learning models for a variety of drug-design applications, using a variety of cutting-edge architectures, including transformers, diffusion networks, GANs, flow networks, etc. (Note that equal levels of familiarity with all the architectures mentioned above is not expected.)
• Lead large-scale model training efforts on multi-GPU compute clusters, including experiments that span weeks to months
• Design methods that couple physics-based simulation (molecular dynamics, quantum calculations, Monte Carlo methods) with learned models
• Prototype and develop methods for using the models you build in structure-based drug design
• Design the datasets, splits, and benchmarks that models are trained and evaluted on — which data, which labels, and which held-out sets reflect real prospective use across protein structures, small molecules, molecular descriptors, and simulation trajectories
• Design validation that reflects prospective use, including scaffold and temporal splits, applicability domain, and calibrated uncertainty, and be candid about where a model should not be trusted
• Partner with drug designers to turn target-specific questions into tractable ML problems, driving innovation in AI/ML approaches to undruggable targets and data-poor target spaces
• Mentor scientists and contribute to the scientific direction and technical strategy for our in silico platform and AI capabilities
• Uphold reproducibility and experimental rigor through experiment tracking, model versioning, code review, testing, and documentation
• Stay current with the literature and publish or present work where appropriate