ML Scientist I​/II, Foundation Models Life Sciences

Position: ML Scientist I / II, Foundation Models for Life Sciences
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), the Foundation Models team researches and develops large-scale generative models and reasoning frameworks that power automated scientific discovery across Lila's life science domains.

We are seeking a Scientist I or II to join this team as a contributor to foundation model research at the intersection of machine learning and life science data. You will work on generative models spanning biological sequences, molecular structures, and multimodal experimental data, contributing to problem formulation, model design, training, evaluation, and integration into Lila's closed-loop discovery engine.

This is an IC role for someone building deep expertise in generative AI applied to biology. You will own research sub-problems end to end, collaborate closely with experimental scientists to close the computational-experimental loop, and contribute to Lila's presence in the broader scientific community.

What You'll Be Building

• Contribute to research on foundation models for life science applications, including biological sequence design, structure prediction, and multimodal scientific reasoning
• Design, train, and evaluate generative models on biological and chemical data, incorporating domain-specific constraints and priors
• Be part of the end-to-end ML process within Lila's "Lab-in-the-Loop" lifecycle: support data generation strategy, build pipeline models, and help design feedback loops where experimental results improve model performance
• Translate biological questions into well-defined ML problems and interpret model outputs in collaboration with wet-lab scientists and computational biologists
• Support research quality and methodology standards within the foundation models program

What You'll Need to Succeed

• PhD in Computer Science, Machine Learning, Computational Biology, or a related quantitative field (or Master's with equivalent research experience)
• Strong foundation in generative model architectures and training, with hands-on experience in model development and evaluation
• Ability to formulate and execute research independently, from problem definition through experimentation
• Familiarity with at least one life science domain (molecular biology, genomics, protein engineering, nucleic acid design, or related)
• Experience collaborating with experimental scientists or working with biological/chemical data
• Proficiency in ML frameworks (PyTorch, JAX, or Tensor Flow) and experience with GPU-based training workflows

Bonus Points For

• Experience in computational protein design or molecular structure prediction
• Experience with active learning loops or closed-loop experimental workflows
• Contributions to open-source ML tools, frameworks, or benchmark datasets for scientific applications
• Familiarity with distributed training infrastructure
• High-impact publications or open-source contributions in AI for Science in relevant venues (NeurIPS, ICML, ICLR, AAAAI, Nature Methods, Nature Biotechnology, or equivalent)

Compensation

We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.

U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.

International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.

-based positions; international salaries are set to local market.

Expected Base Salary Range

$176,000-$304,000 USD

About LILA

Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA…