Senior ML Scientist, Biological Systems
About the role
Lila is redefining the future of medicine by combining automated large-scale data generation with scientific superintelligence. At Lila, we are building the loop where AI, automation, and experimental biology co-evolve to solve the hardest problems in medicine. The Life Science AI team develops machine learning systems for automated reasoning on biological data, combining state-of-the-art ML with breakthrough biology. We seek a Senior ML Scientist to focus on domain models underneath that system: models of perturbation biology, genetics, and high-dimensional experimental readouts that connect biological mechanism, experimental intervention and therapeutic opportunity. At Lila, the data is generated for the model: we run our own experiments at scale, and you will help decide what gets measured. The question is not only what to learn from a fixed dataset, but what datasets should exist. Model outputs are reasoned over; predictions go to systems and scientists choosing what to run next and making mechanistic calls downstream. Both need to know why, not only what. A model that returns a quantity a biologist, human or AI, can argue with; models that transfer to new contexts, compose into a downstream calculation, and can be checked against an independent measurement are often worth more than a more accurate one that returns an embedding.
Responsibilities
- Build domain models for perturbation, genetic, and multimodal experimental data, and translate biological questions into rigorous ML problem formulations.
- Where the biology supports it, build models with interpretable structure — representations grounded in the machinery that executes a biological process rather than in cell