Machine Learning Scientist I / II, Protein Design

Lila Sciences
San Francisco
Workplace: OnsiteFull timeUSD 176,000 - 304,000 annuallyFunction: Data Science & Machine LearningSkills: ["Cross-functional communication","Evaluation rigor","Systems thinking"]

Build molecule design capabilities for biologics programs by developing and operationalizing machine learning workflows that generalize across targets. Partner with domain scientists and platform teams to translate constraints into actionable hypotheses, orchestrate design reasoning workflows, and create benchmarks and evaluation infrastructure. Own reproducibility, throughput, and inference cost, turning learned insights into extensible systems that improve downstream decision-making.

Loading

Loading job details...

Preparing the role view and application actions.

FursaFursa
Lila Sciences
Lila Sciences
5 days ago

Machine Learning Scientist I / II, Protein Design

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 11 hours agoStatus: Live

Job Summary

Build molecule design capabilities for biologics programs by developing and operationalizing machine learning workflows that generalize across targets. Partner with domain scientists and platform teams to translate constraints into actionable hypotheses, orchestrate design reasoning workflows, and create benchmarks and evaluation infrastructure. Own reproducibility, throughput, and inference cost, turning learned insights into extensible systems that improve downstream decision-making.
Location: San Francisco
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Entry level

Key Responsibilities

  • •Design molecules for active biologics programs by translating target, mechanism, and experimental constraints into actionable design hypotheses.
  • •Develop reasoning capabilities for drug discovery by orchestrating design workflows.
  • •Design and maintain benchmarks and evaluation infrastructure to assess whether workflows produce generalizable decisions across biologics programs.
  • •Own operations for reproducibility, throughput, and inference cost of computational design workflows.
  • •Partner with domain scientists to prioritize designs and convert their judgment into ML objectives and evaluation criteria.

Pay and Benefits

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

Key Requirements

  • •MS or PhD in computer science, machine learning, computational biology, biophysics, bioengineering, or a similar quantitative field.
  • •Strong software engineering and system design fundamentals.
  • •Rigor in evaluation and dataset design, including benchmarking, validation failure modes, and measuring real decision quality.
  • •Cross-functional communication skills.
  • •Domain expertise in protein sequence, structure, and function.
Experience:AI for ScienceDrug discoveryProtein engineeringProtein designBiologics
Education:
Skills:Cross-functional communicationEvaluation rigorSystems thinking
Languages:English
Tech Stack:GPUDistributed trainingHigh-throughput inferenceMachine learning orchestrationBenchmarksEvaluation infrastructure

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
WebsiteLinkedIn