Senior / Principal ML Scientist, Foundation Models for Life Sciences

About the role

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.

Responsibilities

• Drive research on foundation models for life science applications, including but not limited to biological sequence design, structure prediction, and multimodal scientific reasoning
• Design, train, and evaluate large-scale generative models on biological and chemical data, integrating domain-specific constraints and priors
• Contribute to the end-to-end ML process within Lila's "Lab-in-the-Loop" lifecycle: steer data generation strategy, build pipeline models, and design feedback loops where experimental results improve model performance
• Translate complex biological questions into well-defined ML problems and interpret model outputs in collaboration with wet-lab scientists and computational biologists
• Advance research standards and methodology within the foundation models program, contributing insights that influence approaches across adjacent teams
• Represent Lila's foundation model research externally through publications at premier venues, conference presentations, and community engagement

Requirements

• PhD in Computer Science, Machine Learning, Computational Biology, or a related quantitative field
• Multiple high-impact first-author or senior-author publications at premier venues (NeurIPS, ICML, ICLR, Nature Methods, Nature Biotechnology, or equivalent)
• Deep expertise in large-scale generative model architectures and training, with hands-on experience training models on distributed infrastructure
• Demonstrated ability to formulate and drive research programs independently, from problem definition through publication and deployment
• Fluency across ML and at least one life science domain (molecular biology, genomics, protein engineering, nucleic acid design, or related), with experience designing computational experiments grounded in biological reality
• Strong track record of cross-functional collaboration with experimental scientists, translating between ML and biology
• Expertise in ML frameworks (PyTorch, JAX, or TensorFlow) and experience with large-scale distributed training infrastructure (AWS, GCP, or on-prem clusters)

Bonus Points For

• Experience in computational protein design, particularly antibody and nanobody engineering
• Experience designing biological sequences or molecular structures with demonstrated wet-lab validation
• Contributions to open-source ML tools, frameworks, or benchmark datasets for scientific applications
• Experience with agentic frameworks or active learning loops in scientific contexts
• 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

• 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
• A company subsidized lunch program

International Benefits

• Comprehensive benefits program tailored to your region
• USD salary ranges apply only to U.S.-based positions; international salaries are set to local market

Expected Base Salary Range

$268,000 - $384,000 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 builds systems that can learn for themselves.

Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance.

A Note to Agencies

Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.