Senior ML Scientist, AI for Protein Engineering

The role

This senior individual contributor will develop and apply generative and predictive models for protein engineering. You will own applied ML workflows and collaborate with experimental scientists to connect protein design models into an autonomous science platform.

What you will do

• Own applied ML workflows for protein engineering campaigns.
• Develop and adapt methods for de novo generation, property prediction, candidate selection, and active learning.
• Integrate 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.
• Strong track record applying machine learning to protein design, biologics engineering, or related biomolecular design problems.
• Deep ML expertise with hands-on experience adapting and developing modern AI methods.
• Strong intuition for therapeutic biologics design including sequence, structure, function, developability, and experimental validation.
• Demonstrated ability to drive applied research independently.
• Strong collaboration and communication skills across ML, biology, experimental science, and software teams.

Nice to have

• Direct experience designing antibodies, nanobodies, enzymes, peptides, or other therapeutic proteins for applied or clinical pipelines.
• Experience with structure prediction, generative protein design, diffusion models, flow matching, or protein language models in a production research setting.
• Familiarity with structural biology, conformational dynamics, developability, affinity maturation, or other biophysical constraints.
• Experience closing design-test-learn loops with wet-lab teams.
• 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
• 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.