Genesis pairs frontier AI with world-class drug hunters to discover small molecule medicines. Built on Pearl and GEMS. Partnered with Gilead and Incyte. Backed by a16z.
About the role
This is a builder–integrator role inside a deeply technical, cross-domain environment spanning AI/ML, engineering, computational chemistry, biology, and wet lab operations. You will serve as the connective tissue and acceleration engine across these domains. You will work closely with senior leadership to own roadmap definition and execution across critical internal platforms while driving structural improvements in how our teams operate.
What they're looking for
- 5+ years of product management experience in a technical or scientific environment
- Bachelor’s degree in Computer Science, Engineering, Chemistry, or related field (advanced degree preferred)
- Strong understanding of machine learning systems and data infrastructure
- Literacy in drug discovery, structural biology, or computational chemistry
- Proven ability to operate at the interface of ML and life sciences
- Demonstrated experience translating computational results into actionable scientific outcomes
More about this role
Genesis Molecular AI is pioneering a transformative approach to drug discovery by leveraging state-of-the-art machine learning, computational chemistry, and biology. Our mission is to accelerate the development of life-changing therapies by merging cutting-edge technology with innovative science. We are building a world-class team to drive forward the future of drug discovery.
We are a mission-driven group of scientists and engineers using cutting-edge computational methods to discover drugs for unmet medical needs. Our work spans machine learning, computational chemistry, biology, and wet lab experimentation , all operating within a high-trust, deeply technical environment.
You’ll join a team with extremely strong ML talent that is actively pushing the frontier of AI in drug discovery . We are refining how experimental data, biological context, and computational models integrate into a seamless feedback loop.
You will help reshape how data flows from experiment → infrastructure → model → decision and increase the speed and scale at which we learn.
This is a builder–integrator role inside a deeply technical, cross-domain environment spanning AI/ML, engineering, computational...
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