Impress employers and recruiters.
Choose from hundreds of resume examples.
Impress employers and recruiters.
Choose from hundreds of resume examples.
Tailor your resume to this Senior ML Scientist, AI for Protein Engineering role.
Rezi rewrites your resume against Lila Sciences's job description. Free.
Tailor your resume to this Senior ML Scientist, AI for Protein Engineering role.
Rezi rewrites your resume against Lila Sciences's job description. Free.
Don't guess if your resume is good enough.
See how it scores against the Senior ML Scientist, AI for Protein Engineering posting at Lila Sciences — free, in seconds.
Don't guess if your resume is good enough.
See how it scores against the Senior ML Scientist, AI for Protein Engineering posting at Lila Sciences — free, in seconds.
About the Role
Lila is building a platform where AI and automation co-evolve to solve the hardest problems in medicine. Within Life Sciences AI, the AI for Protein Engineering team develops and applies generative and predictive models that move biomolecule design programs from in silico hypothesis to wet-lab validated leads. This role sits at the intersection of machine learning, protein engineering, and therapeutic design, collaborating with experimental scientists, AI researchers, and platform teams.
Responsibilities
- Own applied ML workflows for protein engineering campaigns, from design specification through experimental learning.
- Develop and adapt methods spanning de novo generation, sequence- or structure-based property prediction, candidate selection, and active learning.
- Integrate these methods into robust software systems and broader reasoning models.
- Translate therapeutic and biological questions into well-defined ML problems, model outputs, and evaluation plans.
- Partner with experimental scientists to interpret why designed biomolecules succeed or fail, then turn those insights into better models and design principles.
- Build rigorous evaluation frameworks for model generalization to challenging biologics design problems.
Requirements
- PhD in Computational Biology, Computer Science, Machine Learning, Biophysics, Bioengineering, or a related quantitative field.
- Strong track record applying machine learning to protein design, biologics engineering, or related biomolecular design problems, with industry experience strongly preferred.
- Deep ML expertise, with hands-on experience adapting and developing modern AI methods rather than only applying them off the shelf.
- Strong intuition for therapeutic biologics design, including sequence, structure, function, developability, and experimental validation considerations.
- Demonstrated ability to drive applied research independently, from problem definition through experimental validation and iteration.
- Strong collaboration and communication skills across ML, biology, experimental science, and software teams.
Skills
- Direct experience designing antibodies, nanobodies, enzymes, peptides, or other therapeutic proteins for applied or clinical pipelines.
- Experience with structure prediction, generative protein design, diffusion models, flow matching, or protein language models in a production research setting.
- Familiarity with structural biology, conformational dynamics, developability, affinity maturation, or other biophysical constraints.
- Experience closing design-test-learn loops with wet-lab teams, including experimental prioritization, high-throughput validation, and active learning.
- Publications, open-source contributions, or applied research outputs in AI for science venues.
Work Type
- full-time
Experience Level
- senior individual contributor
Education Level
- PhD
Salary/Compensations
- $268,000—$358,000 USD
Benefits
- Competitive base compensation with bonus potential and 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.
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.
- 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.