AI Scientist: Foundation Models for Drug Discovery

Initial Therapeutics, Inc.; San Francisco (CA); Hybrid; USD 168,000 - 268,000; Full time

Benefits offered by this job

Company bonus

401(k) plan

Health, dental, vision benefits

Flexible benefits (FSAs/HSAs)

Life insurance

Well-being benefits

Paid time off

Job summary

Lilly is recruiting an Advisor - AI Scientist to design, train, and evaluate foundation models for chemistry and biology. You will work at the intersection of machine learning, chemistry, biology, and physics, using Lilly data to build AI approaches that accelerate drug discovery breakthroughs.

Based in our Silicon Valley hub, this hybrid role combines collaborative research with practical application, offering a comprehensive benefits package and opportunities to publish and contribute to

Qualifications

• PhD in ML, CS, computational chemistry/biology, or a closely related quantitative field.
• 2+ years of relevant research experience beyond the PhD, in industry or in a postdoctoral position.
• Proven publications, patents, or open-source contributions in related areas.

Responsibilities

• Design, train, and evaluate foundation models for chemistry and biology.
• Develop generative and predictive models from Lilly data to advance discovery.
• Collaborate with researchers, engineers and domain experts to apply AI in discovery programs.
• Design robust evaluation strategies linking model performance to experimental outcomes.

Skills

Foundation models

Generative models

Predictive models

ML research

Python

PyTorch

JAX

Computational chemistry/biology

GPU infrastructure

Education

PhD in Machine Learning

Tools

PyTorch

JAX

GPU clusters

Job description

Lilly is recruiting an Advisor - AI Scientist to design, train, and evaluate foundation models for chemistry and biology. You will work at the intersection of machine learning, chemistry, biology, and physics, using Lilly data to build AI approaches that accelerate drug discovery breakthroughs.

Based in our Silicon Valley hub, this hybrid role combines collaborative research with practical application, offering a comprehensive benefits package and opportunities to publish and contribute to