Sr. AI Science Lead

Job ID: R-110899Company: LillyLocation: San Francisco, California, United States of AmericaJob Type: Full TimeCategory: Information TechnologyPosted Date: 2026-09-08At 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. Where AI Meets Medicine: Build the Future of Drug Discovery in the Heart of Silicon Valley!Making medicine that’s never been made means doing what’s never been done. If you’re an engineer, scientist, or builder who thrives on problems no one has solved before, this is your invitation; we want you on the team. We are ready to challenge the status quo and push medicine forward, all in the name of health. Are you up for the challenge? If so, join us! About the Lilly and NVIDIA PartnershipLilly and NVIDIA are launching a new AI co-innovation lab in the heart of Silicon Valley — an up-to-$1 billion, multi-year commitment to solve drug discovery’s toughest challenges. The lab brings Lilly scientists, technologists, chemists and biologists together with NVIDIA engineers under one roof. Together, we are building purpose-built foundation and frontier AI models trained on Lilly data at scale, tightening the feedback loop between automated wet labs and computational dry labs, designing the next generation of medicines for millions of patients across the globe.What You’ll Be DoingAs a Senior AI Science Lead, you will set scientific direction and technical strategy for large-scale AI research programs that advance drug discovery. You will lead a team of AI scientists and AI engineers while driving major initiatives across computational chemistry, computational genomics, and related domains, ensuring alignment between scientific priorities and organizational goals. In partnership with Lilly Research Labs and engineering and technology leaders, you will transform cutting-edge research into scalable capabilities that accelerate scientific impact. This role requires a track record of scientific leadership, strategic influence, and building large-scale AI research programs in the life sciences field.How You’ll SucceedSet the architectural direction for large-scale AI and foundation models trained on Lilly chemical, biological, and experimental data.Lead the design of the discovery learning cycle, connecting model predictions, experimental validation, and data generation to improve scientific outcomes.Establish the scientific direction for next-generation AI methods, advancing model architectures, learning paradigms, and generative approaches while ensuring thorough evaluation against leading academic and industry benchmarks.Design and lead the implementation of large-scale multi-GPU and multi-node AI training and inference systems on high-performance computing, on the most powerful supercomputer of the life sciences industryBuild, mentor, and develop high-performing teams of AI Scientists, AI Engineers, chemists and biologists, advancing scientific excellence and cultivating new research leadersTranslate research breakthroughs into measurable scientific impact through close partnership with Lilly Research Laboratories, engineering teams, and strategic collaborators, including NVIDIA.What You Should BringEstablished scientific leadership with a track record of leading large-scale AI research programs and shaping strategy in chemistry, biology, or drug discovery.Recognized expertise in computational chemistry, computational biology, genomics, molecular design, or related domains, with demonstrated scientific impact.Proficiency in Python and modern machine learning frameworks such as PyTorch, with experience developing and evaluating novel models.Experience in developing foundation models, self-supervised learning approaches, and large-scale generative AI systems, including training and optimization in large-scale distributed compute environments.Demonstrable ability to design rigorous model evaluation strategies, including benchmarking, validation methodologies, and performance assessment frameworks.Solid understanding of experimental biology, chemistry, or drug discovery workflows, with the ability to translate scientific challenges into machine learning solutions.Experience building, mentoring, and developing high-performing technical or scientific teams.Demonstrated commitment to scientific rigor, data integrity, intellectual property protection, and responsible AI practices.Your Basic QualificationsPhD in Machine Learning, Computer Science, Computational Chemistry, Computational Biology, Physics, Statistics, or a closely related quantitative field.6+ years of post-PhD experience advancing machine learning research, including leadership of research programs, technical strategy, and scientific teams in industry or academia.3+ years’ experience leading scientific teams or research programs, including responsibility for technical direction and hiring.Publication record in leading peer-reviewed machine learning conferences, scientific journals, or equivalent research venues.Location & Work FlexibilityThis role is based at our Silicon Valley Hub. We offer a flexible hybrid work model, with three days onsite and two days working remotely each week, supporting both collaboration and work‑life balance.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 () 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 (View email address on click.appcast.io), 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$259,500 - $380,600Full-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.#WeAreLillySkillsmachine learningpythonfoundation modelspytorchcomputational chemistrycomputational biologygenomicsmolecular designself-supervised learningdistributed computingmodel evaluationbenchmarkingexperimental biologychemistrydrug discoveryteam leadershipscientific strategymentoringtechnical strategyscientific impact translationdata integrityintellectual property protectionresponsible ai