Teams at Chai Discovery

Develops methods to improve foundation models for drug discovery through targeted data generation, model evaluations, and post-training recipes. The role collaborates with pre-training researchers, research engineers, and biological scientists to address protein, antibody, and small-molecule modeling problems. Candidates should bring strong quantitative and machine learning expertise, software engineering depth, and familiarity with biological modeling methods such as AlphaFold, RFDiffusion, ProteinMPNN, and ESM.

Conduct pre-training research for foundation models that learn molecular structure and interactions. Design model architectures, training objectives, and data mixes; train large-scale models; analyze training curves; and develop scalable, general methods informed by frontier AI research. Apply theoretical knowledge in computer science, machine learning, mathematics, or physics to advance therapeutic molecular engineering.

Owns complex business operations initiatives end to end, including contract renegotiation, compute-spend management, office moves, recruiting support, supplier decisions, and executive logistics. Partners with founders and functional leaders to identify friction, solve problems quickly, and build scalable operational systems. The role requires a hands-on generalist with commercial judgment, negotiation ability, operational experience, and a bias for action.