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 a senior individual contributor focused on computational biologics design. The work spans active protein engineering programs and new capabilities that improve 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 deep ML judgment, intuition for protein biology, and experience delivering computationally-designed, wet-lab-validated biologics through AI. You’ll collaborate with experimental scientists, AI researchers, and platform teams to connect specialist protein design models into Lila’s broader autonomous science platform.

What You'll Be Building

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.

ML Scientist I/II, AI for Protein Engineering

Responsibilities

Qualification

Required

Preferred

Benefits

Company

Lila Sciences

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