Head of Drug Discovery, Small Molecules

We are building AI systems that can carry out scientific research. You will lead our small-molecule drug discovery efforts: choosing valuable problems, defining discovery programs, and advancing compounds through experimental validation.

Working directly with the founders and AI researchers, you will own the scientific direction and execution of internal and partnered programs. You will decide what to pursue, which compounds to make and test, and when the evidence supports advancing or stopping a program. You will also develop relationships with biotech, pharma, and academic collaborators to originate programs and help turn successful work into discovery or licensing partnerships.

• Select targets and discovery opportunities with compelling biology, tractable chemistry, and a clear path to valuable drug IP.
• Define program objectives, experimental plans, budgets, and milestones; lead hit finding and lead optimization.
• Direct external chemistry and biology teams, including CROs, to synthesize compounds, run assays, and generate reliable data.
• Work with our AI team to guide molecular design, evaluate predictions against experiments, and improve the next round of decisions.
• Build scientific relationships and develop partnerships alongside the founders, while helping grow our discovery team.

You should be comfortable personally leading discovery decisions in a small team and taking responsibility for experimental outcomes.

Strong candidates will bring:

• A track record of advancing small-molecule programs through hit-to-lead or lead optimization in biotech or pharma.
• Deep expertise in medicinal chemistry or small-molecule discovery, with sound judgment across biology, pharmacology, and DMPK.
• Experience directing synthesis and assay work, interpreting conflicting results, and making difficult program decisions.
• Relationships with discovery leaders and collaborators, and the initiative to turn those relationships into new opportunities.

A PhD or equivalent industry experience is preferred. Experience with computational drug discovery, AI methods, or licensing partnerships is valuable.