AI Scientist; Model Building & Training

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.

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!

Lilly 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.

As an Advisor - AI Scientist, you will design, train, and evaluate foundation models that advance scientific discovery across chemistry and biology. Working at the intersection of machine learning, chemistry, biology, and physics, you will conduct fundamental research to develop AI approaches that deepen our understanding of molecular and biological systems. Using Lilly's proprietary experimental data, you will build and validate generative and predictive models that help transform scientific insights into drug discovery breakthroughs.

• Advance the state of the art in AI for drug discovery by designing and developing generative and predictive models for molecular, chemical, and biological systems.
• Translate machine learning into scientific impact across challenges such as molecular design, target identification, genomics, and structure-based discovery.
• Design rigorous evaluation strategies that connect model performance to meaningful scientific and experimental outcomes.
• Partner closely with researchers, engineers, and domain experts to accelerate the application of AI in discovery programs.
• Drive research from concept to impact, balancing scientific innovation with practical application.

• Deep expertise in computational chemistry/biology, genomics, or a related scientific field.
• Recognized expertise in ML research, with significant contributions to generative, predictive, or foundation models for scientific applications.
• Shown impact through publications at leading research venues, patents, open-source contributions, or other notable scientific achievements.
• Advanced proficiency in Python and modern machine learning frameworks (e.g., PyTorch or JAX), with the ability to independently design, implement, train, and evaluate AI models.
• Experience leading complex research initiatives from hypothesis through scientific validation and impact.
• Demonstrated ability to collaborate across scientific and technical disciplines and communicate complex findings to diverse…