Co-op, Agentic and Generative Protein Design

Lila Sciences • Cambridge, MA

2d

About The Position

Lila Sciences is seeking a co-op to work on AI methods for therapeutic protein design in close collaboration with a wet lab. The role may focus on generative models and protein design pipelines, AI agents for protein design campaigns, or a combination of both. The co-op will own a well-scoped project and deliver code and analyses that inform real design decisions and scientific outcomes.

On the generative-models track, the co-op will build, benchmark, and improve methods for designing proteins such as antibodies and minibinders, with candidates tested in the lab and results grounded in experimental data. On the AI-agents track, the co-op will build and evaluate agents that help plan campaigns, select targets and epitopes, choose methods and settings, launch design and filtering runs, diagnose failures, adapt subsequent rounds, and reason over biological literature alongside outputs from domain-specific models.

Lila Sciences is building Scientific Superintelligence™ by combining advanced AI models with proprietary AI Science Factory™ instruments to execute the scientific method autonomously and accelerate discovery across medicine, materials, and energy. The company is guided by truth, trust, curiosity, grit, and velocity, and is committed to equal employment opportunity.

Requirements

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

Nice To Haves

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

Responsibilities

• Develop, evaluate, and apply agentic systems for protein design and/or deep generative models for protein design.
• Build, benchmark, and improve protein-design methods and pipelines, including approaches for antibodies and minibinders.
• Build and evaluate AI agents to plan and execute protein-design campaigns.
• Support campaign planning, including target and epitope selection and the choice of methods and settings.
• Launch design and filtering runs, diagnose failures, and adapt subsequent campaign rounds.
• Enable agents to reason over biological priors from literature alongside outputs from domain-specific models.
• Own a well-scoped project and deliver code and analyses that inform design decisions and scientific outcomes.

What This Job Offers

• Job Type: Full-time
• Career Level: Intern
• Education Level: No Education Listed