ML Scientist I/II, AI for Protein Engineering

Lilasciences
Location
San Francisco, CA USA
Job Type
Full-time
Posted
September 15, 2026
Views
6

Job Description

Your Impact at LILA

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.

We are looking for an ML Scientist I/II focused on AI for protein engineering. The work spans active protein engineering programs and focused technology development that improves how Lila designs, evaluates, and learns from biomolecular sequence, structure, and function data.

This role sits at the intersection of machine learning, protein engineering, and therapeutic design. The ideal candidate brings strong ML fundamentals, curiosity about protein biology, and interest in computationally designed, wet-lab-validated biologics. You’ll collaborate with experimental scientists, AI researchers, and platform teams to build models and workflows that support Lila’s broader autonomous science platform.

What You'll Be Building

  • Build 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 protein design 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 model improvements.
  • Build evaluation frameworks for model generalization to challenging biologics design problems.

What You'll Need to Succeed

  • 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, or experimental validation considerations.
  • Ability to translate therapeutic or biological objectives into computational design problems and model evaluation plans.
  • Strong collaboration and communication skills across ML, biology, experimental science, and software teams.

Bonus Points For

  • Experience designing antibodies, nanobodies, enzymes, peptides, or other therapeutic proteins.
  • Experience with structure prediction, generative protein design, diffusion models, flow matching, or protein language models.
  • 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.
  • Industry experience translating ML research into practical biological design workflows, experimental campaigns, or platform capabilities.
  • Publications, open-source contributions, or applied research outputs in AI for science venues.

Compensation

We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.

U.S. Benefits.Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.

International Benefits.Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.

Expected Base Salary Range

$176,000—$304,000 USD

About LILA

Your Impact at LILA

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.

We are looking for an ML Scientist I/II focused on AI for protein engineering. The work spans active protein engineering programs and focused technology development that improves how Lila designs, evaluates, and learns from biomolecular sequence, structure, and function data.

This role sits at the intersection of machine learning, protein engineering, and therapeutic design. The ideal candidate brings strong ML fundamentals, curiosity about protein biology, and interest in computationally designed, wet-lab-validated biologics. You’ll collaborate with experimental scientists, AI researchers, and platform teams to build models and workflows that support Lila’s broader autonomous science platform.

What You'll Be Building

  • Build 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 protein design 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 model improvements.
  • Build evaluation frameworks for model generalization to challenging biologics design problems.

What You'll Need to Succeed

  • 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, or experimental validation considerations.
  • Ability to translate therapeutic or biological objectives into computational design problems and model evaluation plans.
  • Strong collaboration and communication skills across ML, biology, experimental science, and software teams.

Bonus Points For

  • Experience designing antibodies, nanobodies, enzymes, peptides, or other therapeutic proteins.
  • Experience with structure prediction, generative protein design, diffusion models, flow matching, or protein language models.
  • 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.
  • Industry experience translating ML research into practical biological design workflows, experimental campaigns, or platform capabilities.
  • Publications, open-source contributions, or applied research outputs in AI for science venues.

Compensation

We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.

U.S. Benefits.Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.

International Benefits.Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.

Expected Base Salary Range

$176,000—$304,000 USD

About LILA

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. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply.

We’re All In

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.

Information you provide during your application process will be handled in accordance with ourCandidate Privacy Policy.

A Note to Agencies

Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.

Frequently Asked Questions

Where is the job located, and is it remote/hybrid/on-site?
The job is located in San Francisco, CA USA. The posting does not specify a remote or hybrid work-mode policy, but it notes that commuter benefits are available for office-based employees.
What are the required qualifications and experience level for this role?
You need a PhD in Computational Biology, Computer Science, Machine Learning, Biophysics, Bioengineering, or a related quantitative field. You must also have experience applying machine learning to protein design or biomolecular design, strong ML fundamentals, fluency with biological sequence/structure data, and the ability to translate biological objectives into computational problems.
What are the key responsibilities of the ML Scientist?
You will build ML workflows for protein engineering, develop and adapt methods for de novo generation and property prediction, integrate protein design methods into software systems, translate biological questions into ML problems, and partner with experimental scientists to interpret wet-lab results and improve models.
What is the salary range for this position?
The expected base salary range for this U.S.-based position is $176,000 to $304,000 USD. The company also offers bonus potential and early-stage equity.
What benefits does Lilasciences offer to U.S. employees?
U.S. benefits include medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off and company holidays; paid parental leave; educational assistance; commuter benefits (including bike share memberships); and a subsidized lunch program.

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Job Information

Source: greenhouse
AI Relevance: 95/100 (Highly relevant)
Remote Type: onsite
Allowed Locations: San Francisco, CA USA
Skills & Tags:
AI

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