ML Scientist I/II, AI for Protein Engineering

Lila Sciences
San Francisco
Workplace: OnsiteFull timeUSD 176,000 - 304,000 annuallyFunction: Research & Scientific (R&D)Education: phdSkills: ["Collaboration","Communication","Problem-solving"]

Build machine learning workflows for AI-driven protein engineering campaigns, from design specification through experimental learning. Develop methods for de novo generation, property prediction from sequence/structure, candidate selection, and active learning. Integrate protein design approaches into robust software systems, translate therapeutic goals into ML problems and evaluation plans, and partner with experimental scientists to improve models using design-test-learn feedback. Create evaluation frameworks for hard biologics design cases.

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Lila Sciences
Lila Sciences
2 days ago

ML Scientist I/II, AI for Protein Engineering

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Source: Company careers pageValidated by: Fursa AI
Last checked: 10 hours agoStatus: Live

Job Summary

Build machine learning workflows for AI-driven protein engineering campaigns, from design specification through experimental learning. Develop methods for de novo generation, property prediction from sequence/structure, candidate selection, and active learning. Integrate protein design approaches into robust software systems, translate therapeutic goals into ML problems and evaluation plans, and partner with experimental scientists to improve models using design-test-learn feedback. Create evaluation frameworks for hard biologics design cases.
Location: San Francisco
Workplace: Onsite
Employment Type: Full time
Job Function: Research & Scientific (R&D)
Seniority: Mid level

Key Responsibilities

  • •Build ML workflows for protein engineering campaigns, from design specification through experimental learning.
  • •Develop and adapt approaches for de novo generation, property prediction, candidate selection, and active learning.
  • •Integrate protein design methods into robust software systems and broader reasoning models.
  • •Translate therapeutic/biological questions into ML problems, model outputs, and evaluation plans.
  • •Partner with experimental scientists to interpret design outcomes and turn insights into model improvements and generalization evaluation.

Pay and Benefits

Salary: USD 176,000 - 304,000 annually
Equity and Bonus:Equity
Perks:Health InsuranceDentalVisionLife InsuranceDisability InsurancePaid ParentalLearning BudgetCommuter BenefitsMeal Allowance

Key Requirements

  • •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, and/or experimental validation considerations.
  • •Ability to translate therapeutic or biological objectives into computational design problems and model evaluation plans.
Experience:Protein engineeringBiologicsAI for scienceWet-lab validation
Education:PhD / Doctorate
Skills:CollaborationCommunicationProblem-solving
Languages:English
Tech Stack:Machine learningProtein designActive learningDe novo generationSequence-based property predictionStructure-based property predictionGenerative protein designDiffusion modelsFlow matchingProtein language modelsStructure prediction

Company Brief

Lila Sciences
Develops AI-driven platforms to accelerate drug discovery and biological research by integrating machine learning with chemical and biological data to predict molecular properties, streamline candidate selection, and enable faster therapeutic development.
Industry: Biotech
Company Size: Small (11 to 50 employees)
Growth: Early Stage Startup
Funding: Seed
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