Protein Design ML Scientist I/II — AI for Biologic Design

Lilasciences; San Francisco (CA); On-site; USD 176,000 - 304,000; Full time

Benefits offered by this job

Medical, dental, and vision coverage

Life and disability insurance

Generous holidays

Parental leave

Educational assistance

Commuter benefits

Lunch program

Job summary

Lila Sciences is seeking an ML Scientist I/II focused on AI for protein engineering. You will work at the intersection of machine learning, protein design, and therapeutic development, building models and workflows that advance biomolecule design from in silico ideas to wet-lab validation with experimental partners.

Collaborate with experimental scientists and platform teams, translate biological questions into computable design problems, and contribute to robust software systems.

Qualifications

• PhD in a quantitative field (Computational Biology, CS, ML, Biophysics, Bioengineering)
• Experience applying ML to protein design or related biomolecular design
• Strong ML fundamentals with hands-on model development and evaluation
• Fluency with sequence, structure, function, developability, or experimental validation

Responsibilities

• Build ML workflows for protein engineering campaigns from design to experimental learning
• Develop and adapt methods spanning de novo generation, sequence/structure-based prediction, and active learning
• Integrate protein design methods into robust software systems and broader reasoning models
• Translate therapeutic questions into well-defined ML problems and evaluation plans
• Collaborate with experimental scientists to interpret results and improve models
• Create evaluation frameworks for model generalization to challenging biologics design problems

Skills

ML fundamentals

Protein design

Collaboration

Biology concepts

Education

PhD in Computational Biology/CS/ML/Bioengineering

Tools

Python

ML frameworks (PyTorch/TensorFlow)

Job description

Lila Sciences is seeking an ML Scientist I/II focused on AI for protein engineering. You will work at the intersection of machine learning, protein design, and therapeutic development, building models and workflows that advance biomolecule design from in silico ideas to wet-lab validation with experimental partners.

Collaborate with experimental scientists and platform teams, translate biological questions into computable design problems, and contribute to robust software systems.