Machine Learning Scientist I / II, Protein Design
$176k - $304k • San Francisco, CA USA • Full-time
Posted 1mo ago
Remote Work Policy
On-site
Employment Type
Full-time
Categories
Machine Learning Engineer
About the job
Lila Sciences is building a platform where AI and automation co-evolve to solve complex problems in medicine, specifically in protein engineering. The AI for Protein Engineering team develops models and systems to advance biologics from design to validation. This role involves designing molecules for active biologics programs, developing reasoning capabilities for drug discovery, and creating evaluation infrastructure to ensure design workflows are effective and generalizable across programs. The position requires owning the operational aspects of computational design workflows, including reproducibility, throughput, and inference cost, and translating domain scientist judgment into machine learning objectives.
Responsibilities
- Design molecules for active biologics programs, partnering with domain scientists to translate target, mechanism, and experimental constraints into actionable design hypotheses.
- Develop reasoning capabilities for drug discovery, including orchestrating design workflows.
- Design and maintain benchmarks and evaluation infrastructure to measure the effectiveness and generalizability of design workflows.
- Own operations around reproducibility, throughput, and inference cost of computational design workflows.
- Work with domain scientists to understand design prioritization and translate that judgment into ML objectives and evaluation criteria.
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, understanding how benchmarks can leak and how to measure automated system decision-making.
- Strong cross-functional communication skills.
- Domain expertise in protein sequence, structure, and function.
Benefits
- Competitive base compensation with bonus potential
- Generous early-stage equity
- 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, including bike share memberships for office based employees
- Company subsidized lunch program