Senior / Principal ML Scientist, Foundation Models for Life Sciences at Lila Sciences · LumiJobs

Responsibilities

Lila is building a platform where AI and automation co-evolve to solve the hardest problems in medicine. Within Life Science AI (LSAI), the Foundation Models team builds foundation models that learn across biological sequence, molecular structure, and experimental data to power automated scientific discovery across Lila's life science domains.
We are seeking a Senior or Principal Scientist to set the direction for our work on structure prediction and co-folding. The team's current emphasis is protein–protein and complex prediction in support of antibody and biologics design, and on making those predictions good enough to drive real experimental decisions. You will own models end to end, from problem formulation and architecture through training at scale, evaluation, and integration into Lila's closed-loop discovery engine.
This is a high-impact IC role for someone operating at the frontier of structure-aware generative AI for biology. You will shape the technical agenda for structural foundation model research, collaborate closely with experimental scientists to close the computational–experimental loop, and represent Lila's work to the broader scientific community.
What You'll Be Building
Drive research on structure prediction and co-folding models for protein complexes, protein–protein interactions, and related biomolecular systems
Design, train, and evaluate models that advance the state of the art in AlphaFold-style co-folding, diffusion models, protein language models, and related structure-aware ML methods
Set the evaluation bar for the program, building frameworks that establish model generalization to challenging de novo design problems
Own training, inference, and evaluation at scale across large GPU clusters
Shape the end-to-end ML process within Lila's "Lab-in-the-Loop" lifecycle: steer data generation strategy, build pipeline models, and design feedback loops where experimental results improve model performance
Extend into adjacent foundation model research where it strengthens the structural work, including biological sequence design and multimodal scientific reasoning
Translate complex biological questions into well-defined ML problems and interpret model outputs in collaboration with wet-lab scientists, structural biologists, and computational biologists
Advance research standards and methodology within the foundation models program, contributing insights that influence approaches across adjacent teams

Senior / Principal ML Scientist, Foundation Models for Life Sciences

Responsibilities

Qualification

Required

Preferred

Benefits

Company

Lila Sciences

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