AVP, Generative Design & Optimization, Biotherapeutics

At Lilly, the work is demanding because patients are waiting. We unite caring with discovery to help make life better for people around the world, knowing that every decision, every detail, and every day matters. Headquartered in Indianapolis, Indiana, our over 50,000 employees around the globe take on complex challenges to discover and deliver life-changing medicines, strengthen how health is understood and managed, and support the communities we serve.

This is hard, urgent, selfless work—but it’s work worth doing. If you’re driven by purpose and ready to bring your best to work that truly matters for patients, we invite you to join us.

At Lilly, we unite caring with discovery to make life better for people around the world. For more than 25 years, Lilly’s Biotechnology Discovery Research (BioTDR) organization has advanced novel antibody and peptide therapeutics from concept through clinical development to market in areas of high unmet medical need. This role is based at the Lilly Biotechnology Center in San Diego, where we are expanding our computational capabilities to build a generative design platform.

By bringing together AI/ML, protein engineering, automation, structural biology, and high-throughput experimentation, BioTDR is creating an integrated de novo design platform capable of generating, ranking, and optimizing novel therapeutic antibodies and other biotherapeutics with improved activity, safety, manufacturability, and target coverage. Designs are rapidly evaluated through experimental validation, creating a continuous learning cycle that strengthens both models and discovery outcomes.

The program is supported by dedicated capacity on Lilly Pod, our wholly owned 1,016‑GPU NVIDIA Blackwell Ultra SuperPOD. Help us push the de novo protein design frontier beyond binders to molecules that can become medicines, faster. Ready to make an impact? Join us.

• Advance controllable molecule generation. Translate therapeutic design intent into explicit computational design specifications. Develop approaches for intentional design against defined biological objectives including epitope, molecule format, and therapeutic attributes.
• Define sampling, search, and scoring strategy. Establish approaches that maximize design quality and portfolio impact, determining where increased exploration improves outcomes and where intelligent search provides greater efficiency than brute‑force scaling.
• Lead multi‑objective optimization. Establish Pareto‑based and constraint‑based optimization strategies spanning binding affinity, kinetics, specificity, functional activity, develop ability, immunogenicity, and other therapeutically relevant properties.
• Define data and corpus strategy. Determine how internal and external biological, structural, and experimental data are converted into design‑ready assets that accelerate model performance and therapeutic discovery. Training corpus content and sampling strategy will be jointly governed with the Foundation Models and Active Learning & Design Validation teams.
• Establish an end‑to‑end design pipeline. Build robust workflows spanning epitope definition, conditioned generation, sampling and search, scoring, optimization, diversity selection, and experimental nomination. Ensure workflows are scalable, reproducible, traceable, and adaptable across programs.
• Define success metrics and decision frameworks for generative design performance. Ensure progress is measured against experimental outcomes and therapeutic objectives rather than computational benchmarks alone.
• Build and lead a world‑class organization and provide cross‑functional leadership. Recruit, develop, and retain exceptional…