Co-op, Agentic and Generative Protein Design

Lila Sciences
Lila Sciences logo
Location
Cambridge, MA USA; San Francisco, CA USA
Job Type
Full-time
Posted
November 2, 2026

Job Description

Your Impact at LILA

Our team works on AI methods for therapeutic protein design, with a tight loop between computation and the wet lab. A co-op could take on either of two tracks, or a mix of both. (1) Generative models and protein design pipelines: build, benchmark, and improve methods for designing proteins (such as antibodies and minibinders), with candidates tested in our lab so results are grounded in experimental data. (2) AI agents for protein design campaigns: build and evaluate agents that help plan campaign strategy (target and epitope selection, choosing methods and settings), execute campaigns (launching design and filtering runs, diagnosing failures, adapting the next round), and reason over biological priors from the literature alongside the outputs of domain-specific models. Either way, the co-op would own a well-scoped project, ship code and analyses that feed real design decisions and scientific outcomes.

What You'll Be Building

  • Develop, evaluate, and apply agentic systems for protein design and/or deep generative models for protein design.

What You'll Need to Succeed

  • Strong python and and computational science background.
  • Experience with coding agents.
  • Experience with machine learning for molecular design

Bonus Points For

  • Experience with customizing agents, building harnesses, or using agents for scientific applications
  • Solid technical understand and experience with generative models.

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.

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Frequently Asked Questions

Where is this job located?
The position is located in Cambridge, MA, USA and San Francisco, CA, USA. The job posting does not specify a remote, hybrid, or on-site work policy.
What qualifications are required for this co-op position?
Candidates need a strong Python and computational science background, along with experience using coding agents and machine learning for molecular design.
What additional skills are preferred?
Bonus points are given for experience customizing agents, building harnesses, using agents for scientific applications, and having a solid technical understanding and experience with generative models.
What will my primary responsibilities be?
You will own a well-scoped project developing, evaluating, and applying agentic systems and/or deep generative models for protein design. Tasks include building design pipelines, evaluating agents for planning and executing campaign strategies, and shipping code to inform scientific decisions and experimental wet-lab testing.

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  • 35 open roles
  • Culture, benefits & locations
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Job Information

Source: greenhouse
AI Relevance: 92/100 (Highly relevant)
Remote Type: onsite
Skills & Tags:
AI
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