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About the Role
Lila Sciences is building a platform where AI and automation co-evolve to solve complex problems in medicine. The AI for Protein Engineering team focuses on creating models and systems to advance biologic design from specification to validation. This role involves designing molecules for active biologics programs, developing reasoning capabilities for drug discovery, and ensuring the reproducibility and efficiency of computational design workflows.
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 that measure whether design workflows produce useful, generalizable decisions across biologics programs.
- Own operations around reproducibility, throughput, and inference cost of computational design workflows.
- Work with domain scientists to understand how designs are prioritized and turn 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: how benchmarks leak, why a good validation number fails downstream, and how to measure whether an automated system is making good decisions.
- Strong cross-functional communication skills.
- Domain expertise in protein sequence, structure, and function.
Skills
- Building reasoning models
- Agents
- Planning systems
- Multi-step ML orchestration
- Designing antibodies, nanobodies, enzymes, peptides, or other therapeutic proteins within design-test-learn loops
- Developing evaluation harnesses, model registries, or benchmark suites
- Training or serving models at scale
- Distributed training
- GPU efficiency
- High-throughput inference
- Publications, open-source contributions, or applied research outputs in AI for Science venues
Location
- U.S.
Work Type
- Full-time
Education Level
- MS or PhD in computer science, machine learning, computational biology, biophysics, bioengineering, or a similar quantitative field.
Salary/Compensations
- $176,000—$304,000 USD
Benefits
- 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
- Comprehensive benefits program tailored to their region (International)
About the Company
- Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges.
- We believe science is the most inspiring frontier for AI.
- Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.
- LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy.
- Learn more at www.lila.ai.
- Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance.
Equal Opportunity
- Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.