Job Description

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.

Our protein AI/ML models currently helps design, select, and optimize antibody and peptide leads, with measurable impact on portfolio programs. We are now expanding the computational team to build a generative design platform linking de novo design directly to the biology we want, delivering molecules with better activity, safety, and manufacturability. Targets are chosen by therapeutic need, including difficult classes like GPCRs, and validated designs are advanced directly into Lilly's portfolio.

This role is based at the Lilly Biotechnology Center in San Diego, where computational science, protein engineering, automation, and biology sit in one building. Designs are made and tested here on a fast cycle, and every result, including the negatives, feeds closed-loop learning. You'll train at scale from day one. The program has dedicated capacity on LillyPod, our wholly owned 1,016-GPU NVIDIA Blackwell Ultra SuperPOD. Compute isn't the constraint here, talent is.

Primary Responsibilities

Our Generative Design platform has three pillars: Generative Foundation Models, Generative Protein Design & Optimization, and Active Learning & Design Validation. The AVP of Generative Foundation Models for Biotherapeutics will define and execute a scientific strategy for protein foundation models, starting with antibodies and VHHs and expanding across biotherapeutic modalities as the platform matures. This is a founding role. You'll build the team behind that strategy and stay close enough to the science to shape it directly.

• Set scientific vision and technical roadmap for generative AI and protein foundation models, identifying where new computational approaches can change how therapeutic molecules are discovered and optimized.
• Lead the team to establish and advance structure-based generative models for de novo antibody design.
• Set pretraining and post-training strategy across self-supervised learning, fine-tuning, transfer learning, reward-guided optimization, and reinforcement learning, and decide how proprietary binding, functional, and developability measurements enter training.
• Design and train the confidence heads, with out-of-distribution detection, failure-mode characterization, and applicability-domain assessment against experimental outcomes.
• Set model scaling and infrastructure strategy across data, compute, and training duration.
• Create learning strategies that leverage proprietary biological data, partnering with data, experimental, and scientific teams on multimodal integration to drive increasingly powerful models.
• Build and lead a team of AI researchers and ML infrastructure engineers, and attract and retain top talent.
• Drive cross-disciplinary collaboration, pairing AI researchers with antibody engineers, structural biologists, and therapeutic-area experts so domain insight shapes model development.
• Partner with data engineering, MLOps, and infrastructure teams to keep researchers focused on scientific innovation rather than platform maintenance.
• Represent the organization as a scientific leader, communicating strategy to senior leadership and engaging the broader scientific community through publications, conferences, and collaborations.

Basic Requirements

• Ph.D. in computer science, mathematics, physics, computational biology, or a related quantitative STEM field, with 5+ years post-Ph.D. research experience (or M.S. with 10+ years), including at least 3 years as a formal supervisor.
• First-author or equivalently attributable contribution to a structure-based generative or structure-prediction model for biomolecular complexes, trained at scale.
• Track record in generative or predictive modeling for protein structure, sequence design, or molecular interaction, with first-author or equivalent contributions.
• Experience training deep learning models at scale on multi-node GPU infrastructure, with fluency in Python and PyTorch and the depth to challenge architecture and training decisions directly.

Additional Preferences

• Demonstrated ability to influence at the senior-executive level, including presenting research strategy and compute or headcount requests to decision-makers.
• Experience leading research in a large, matrixed organization and operating through ambiguity.
• Depth in equivariant architectures, diffusion or flow matching on structure, and graph transformers, with hands-on work in all-atom generation, side-chain packing, or inverse folding.
• Experience validating uncertainty quantification against experimental outcomes, not just held-out structures.
• Track record of leading a de novo binder or antibody design effort into a discovery portfolio. Antibody or VHH experience is a plus but not required.
• Experience improving model efficiency, and a released method or model other groups now benchmark against.
• Track record recruiting senior AI research talent and building a research team from scratch, including first hires and technical standards.
• Experience owning a large GPU allocation or shared compute platform, and working in a co-innovation or strategic partnership with a compute, platform, or lab-automation partner.

Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.

Lilly is proud to be an EEO Employer and does not discriminate on the basis of age, race, color, religion, gender identity, sex, gender expression, sexual orientation, genetic information, ancestry, national origin, protected veteran status, disability, or any other legally protected status.

Our employee resource groups (ERGs) offer strong support networks for their members and are open to all employees. Our current groups include: Africa, Middle East, Central Asia (AMECA), Black Employees at Lilly (BE@Lilly), Chinese Culture Network (CCN), EnAble, Evolve, Lilly Indian Network (LIN), Organization of Latinx at Lilly (OLA), Pride (LGBTQ+ Allies), Veterans Leadership Network (VLN) and Women’s Initiative for Leading at Lilly (WILL).

Actual compensation will depend on a candidate’s education, experience, skills, and geographic location. The anticipated wage for this position is

$267,000 - $391,600

Full-time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance). In addition, Lilly offers a comprehensive benefit program to eligible employees, including eligibility to participate in a company-sponsored 401(k); pension; vacation benefits; eligibility for medical, dental, vision and prescription drug benefits; flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts); life insurance and death benefits; certain time off and leave of absence benefits; and well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities).Lilly reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion and Lilly’s compensation practices and guidelines will apply regarding the details of any promotion or transfer of Lilly employees.

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