Machine Learning Scientist, BioML

The role

You will work at the intersection of mechanistic modeling and experimental design to build a biological mechanism layer for an AI and automation platform. You will encode mechanistic reasoning into systems, analyze biological data, and design experimental campaigns to close the loop.

What you will do

• Encode mechanistic reasoning into systems and build evaluations
• Analyze biological data including single-cell, perturbation, proteomics imaging, and genetic data
• Build pipelines to turn raw measurement into model-ready evidence
• Design experimental campaigns to anchor systems in real data
• Build outcome-verifiable benchmarks and evidence standards
• Co-design with ML scientists, engineers, and experimental scientists
• Communicate results to scientific, engineering, and therapeutic audiences

Required qualifications

• PhD in Computational Biology, Bioinformatics, Computational Genomics, Biostatistics, Machine Learning, or a related quantitative field
• Research centered on biological data
• Fluent Python
• Substantial experience analyzing high-dimensional biological data (single-cell omics, perturbation screens, imaging-based proteomics, or genetics) in reproducible, version-controlled pipelines
• Mechanistic biology fluency
• Ability to assess whether data support a claim and reason about what was knowable
• Ability to explain methods, assumptions, results, and limitations to technical and interdisciplinary audiences

Nice to have

• Deep analysis experience in at least one of: perturbation screens, single-cell omics, imaging-based proteomics, or functional genomics
• Depth in immune cell biology, cell therapy, or targeted delivery — receptor engagement, trafficking, or effector function
• Experience with lab-in-the-loop or closed-loop workflows, active learning, or experiment selection
• Experience evaluating language models or agents on scientific judgment tasks, including contamination and memorization controls
• Experience designing or applying structured evidence frameworks, curated resources, or controlled vocabularies

Benefits

• Medical, dental, and vision coverage
• Employer-paid life and disability insurance
• Flexible time off with generous company wide holidays
• Paid parental leave
• Educational assistance program
• Commuter benefits, including bike share memberships for office based employees
• Company subsidized lunch program

About the company

Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. The company combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science.