Senior ML Scientist, Biological Systems

Your Impact at LILA Lila is building a platform where AI and automation co-evolve to solve the hardest problems in medicine. Within Life Science AI (LSAI), we develop autonomous-science capabilities for cellular and tissue biology, spanning single-cell omics, perturbation biology, spatial profiling, imaging, genetics, and multi-modal experimental data that integrate deep biological expertise with foundation modeling and agentic systems. We are seeking a Senior Machine Learning Scientist to help execute this vision by building autonomous life science systems grounded in epistemology, scientific methodology, Bayesian argumentation, and automation. This role will translate the scientific direction of Autonomous Life Science AI into working architectures, workflows, and evaluation methods that allow AI systems to reason rigorously about biological hypotheses, propose experiments, incorporate evidence, and accelerate discovery. This is a hands-on scientific and technical role for someone who can operate at the intersection of machine learning, biological reasoning, agentic systems, and experimental design. The right person will be comfortable formalizing how scientific knowledge is represented, how uncertainty is handled, how evidence changes belief, and how automated systems can execute increasingly rigorous cycles of life science discovery. What You'll Be Building Build autonomous life science systems that connect AI reasoning, biological evidence, experimental design, and automated execution. Translate the broader Autonomous Life Science AI vision into concrete architectures, workflows, prototypes, and production-quality research systems. Develop methods for representing hypotheses, uncertainty, evidence, and scientific arguments in ways that enable robust machine reasoning. Apply Bayesian reasoning, epistemology, and scientific methodology to the design of AI systems that can propose, test, and revise biological hypotheses. Design agentic workflows that plan experime