Machine Learning Scientist, AI for Protein Engineering

The role

This person will build ML workflows for protein engineering campaigns and develop methods for de novo generation and property prediction. They will collaborate with experimental scientists to translate biological questions into ML problems and build evaluation frameworks.

What you will do

• Build ML workflows for protein engineering campaigns
• Develop and adapt methods for de novo generation, property prediction, and active learning
• Integrate protein design methods into software systems and reasoning models
• Translate therapeutic and biological questions into ML problems and evaluation plans
• Partner with experimental scientists to interpret biomolecule success or failure
• Build evaluation frameworks for model generalization

Required qualifications

• PhD in Computational Biology, Computer Science, Machine Learning, Biophysics, Bioengineering, or a related quantitative field
• Experience applying machine learning to protein design, biologics engineering, or related biomolecular design problems
• Strong ML fundamentals with hands-on experience developing, adapting, training, or evaluating modern AI methods
• Fluency with biological sequence, structure, function, developability, or experimental validation considerations
• Ability to translate therapeutic or biological objectives into computational design problems and model evaluation plans
• Strong collaboration and communication skills across ML, biology, experimental science, and software teams

Nice to have

• Experience designing antibodies, nanobodies, enzymes, peptides, or other therapeutic proteins
• Experience with structure prediction, generative protein design, diffusion models, flow matching, or protein language models
• Familiarity with structural biology, conformational dynamics, developability, affinity maturation, or other biophysical constraints
• Experience closing design-test-learn loops with wet-lab teams
• Industry experience translating ML research into practical biological design workflows, experimental campaigns, or platform capabilities
• Publications, open-source contributions, or applied research outputs in AI for science venues

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.