lilasciences · San Francisco, CA USA
Your Impact at LILA 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 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. And 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. What You'll Be Building 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-type identity embeddings, and parameters a biologist can argue with. Make uncertainty a deliverable. …truncated… ence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into t…
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