Senior ML Scientist, AI for Protein Engineering
San Francisco, CA$268k - $358kfull-timePosted 1mo ago
About the role
Senior individual contributor focused on computational biologics design within the Life Sciences AI, AI for Protein Engineering team. Develops and applies generative and predictive models to design, evaluate, and learn from biomolecular sequence, structure, and function data, delivering computationally-designed, wet-lab-validated biologics.
Responsibilities
- Own applied ML workflows for protein engineering campaigns, from design specification through experimental learning.
- Develop and adapt methods spanning de novo generation, sequence- or structure-based property prediction, candidate selection, and active learning. Integrate these methods into robust software systems and broader reasoning models.
- Translate therapeutic and biological questions into well-defined ML problems, model outputs, and evaluation plans.
- Partner with experimental scientists to interpret why designed biomolecules succeed or fail, then turn those insights into better models and design principles.
- Build rigorous evaluation frameworks for model generalization to challenging biologics design problems.
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, with industry experience strongly preferred.
- Deep ML expertise, with hands-on experience adapting and developing modern AI methods rather than only applying them off the shelf.
- Strong intuition for therapeutic biologics design, including sequence, structure, function, developability, and experimental validation considerations.
- Demonstrated ability to drive applied research independently, from problem definition through experimental validation and iteration.
- Strong collaboration and communication skills across ML, biology, experimental science, and software teams.
Skills
Required:Applied machine learning for protein designProblem formulation and evaluationCollaboration across ML, biology, and experimental teams
Benefits
- 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.
Last updated Sep 16, 2026. Interested? Apply on the company site.
About Lila Sciences
Pioneering Scientific Superintelligence
Pioneering Scientific Superintelligence to solve humankind’s greatest challenges.
Scientific SuperintelligenceAIAutonomous LabsLife SciencesChemical SciencesMaterials Sciences
More open roles at Lila Sciences
- Staff IT Systems Engineer, Endpoints4d agoCambridge, MA · Business Operations
- Principal Network Engineer4d agoCambridge, MA · Business Operations
- Contractor, P2P Specialist4d agoCambridge, MA · Corporate Development
- Staff / Principal Research Engineer, AI Safety Mitigations4d agoHybrid (Cambridge, MA; London, UK; San Francisco, CA) · AI
- Specialist / Senior Procurement Specialist4d agoCambridge, MA · Corporate Development