Machine Learning Scientist I/II, AI for Life Sciences
About The Position
Lila is embarking on a transformative mission to redefine the future of medicine by combining automated large-scale data generation with scientific superintelligence. At Lila, we don't just use AI to analyze biology; we are building the loop where AI and automation co-evolve to solve the hardest problems in medicine. To this end, we are forming a new function, Life Science AI (LSAI), with the goal of researching automated reasoning on biological data by combining state-of-the-art machine learning with breakthrough biology. We are seeking world-class ML Research Scientists to join the founding LSAI team. You will be the driver and engine of our scientific superintelligence, moving between deep theoretical research and the practical deployment of models. Whether you are a hands-on IC pushing the boundaries of SOTA ML or a technical lead guiding a high-velocity research pod, we have a place for your expertise.
Requirements
- Education: PhD in Computer Science, Machine Learning, Computational Biology, or a related quantitative field.
- Research Excellence (Level I): We require at least one first-author paper in a premier venue: ML Focus: ICLR, ICML, or NeurIPS (Full track). Biology/Nature Focus: Nature, Science, Cell, or specialized titles (Nature Methods, Nature Biotechnology, Nature Medicine).
- Scientific Vision: We seek individuals whose work demonstrates the potential to be (or is already recognized as) a seminal contribution to the field, fundamentally aligned with Lila's vision of automated reasoning.
Nice To Haves
- Advanced Experience (Level II/III): Beyond the initial track record, we look for multiple high-impact contributions, industry pipeline accomplishments, and/or proven expertise in technical project leadership.
Responsibilities
- Model Architecture & Research: Lead the design, training, and evaluation of large-scale generative models and reasoning frameworks for biological data.
- The "Lila Loop" Execution: Collaborate directly with experimentalists to design and optimize the Lila "Lab-in-the-Loop" lifecycle. You will own the end-to-end ML process, from steering data generation to designing pipeline models integrated into our automated closed-loop discovery engine.
- Bilingual Translation: Translate complex biological questions into well-defined ML problems. You will work side-by-side with wet-lab scientists to interpret model outputs and refine design strategies.
- Technical Mentorship: (For Group Leads) Provide deep technical guidance to a small team of researchers, ensuring code quality, rigorous benchmarking, and scientific integrity.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
Ph.D. or professional degree
Number of Employees
101-250 employees
