Co-founder & CEO, AI for predictable drug discovery and development

Drug discovery is broken. We're building the AI that fixes it: a closed-loop agentic system that does the scientific reasoning end to end and returns predictions you can trace back to the evidence behind them.

We're looking for a founder and operator to join our technical and product founders. As Co-founder & CEO you take a built, already-used platform from spin-out through a competitive seed round and on to Series A. The company spins out of Deep Science Ventures over the coming months.

Drug discovery is one of the most important problems in the world and one of the least solved. Biology is complex; the useful data is sparse; the work runs in slow cycles of trial and error. Teams spend years and billions of dollars on development, and most of the time the drug still fails.

Brute force will not fix it: more compute and more data have not made biology predictable. Making today's process incrementally faster will not either, because that process is capped by what a human team can hold in their heads. What works is a different way of doing the science itself, an AI framework that reasons through it end to end, drawing on the published literature and the data and closing the loop with the wet lab. It's built around what today's agentic models are good at, and guarded hard where they fail.

The proof of concept is ready and has been tested on several use cases. In a single run it processed an entire disease's single-cell data, ingested hundreds of experimental facts extracted from the literature, built a connected map of the biology and returned drug-target hypotheses. Each hypothesis came back marked supported or refuted, traceable with provenance to the exact evidence behind it. When the data is this thin, that grounding is what separates an answer you can build on from one you take on faith. The work came out of a collaboration with the Allen Institute, and the first results are submitted to a top-tier journal (Cell). Preprint: https://www.biorxiv.org/content/10.64898/2026.07.01.734821v1.

The system already produces strong results for parts of the drug development pipeline, target validation among them, powered by the data modalities we have built in. The plan is to scale that to every modality and reach what the whole field is chasing: reliably predicting what a clinical trial will do before it runs, with a concrete explanation of the biology of why.

We prove things with hard, contamination-free benchmarks rather than decks. We've built a freedom-to-operate benchmark for our internal tool and are working towards a clinical-trial benchmark with mechanistic explanation, because a trial is the one place biology gives a straight answer. An engine validated against that benchmark is more than capable of tackling every stage of drug development, and in time, of showing not just what a trial will do but how to change it.

This is a deeply hands-on role. As Co-founder & CEO you own the commercial and company-building side from day one, working hand in hand with the other founders, who own the platform and the science between them. You will:

• Shape strategy and positioning alongside the founding team.
• Lead fundraising: run a competitive seed round and the path to Series A.
• Build the commercial side: partnerships, pilots and paying customers across pharma and biotech.
• Build the company: hiring, story, board, grants, academic partnerships and daily operations.

• Driven to build a category-defining company at the frontier of AI and drug discovery, and to challenge how the industry works today.
• Impact-driven: you take the initiative, make things happen, and think from first principles about what's really needed.
• Clear entrepreneurial spirit, with the ability to thrive in an ambiguous, unstructured and demanding environment.
• Collaborative by nature: able to partner closely with two founders, one technical and one product.

• World-class expertise in AI, with real ownership behind it: not a seat at a famous lab, but work the field knows is yours. Deep drug-discovery experience can stand in its place if your name raises money, but AI is what we're searching for.
• Either you have personally led a priced round, or your name and track record make one raisable.
• Able to go full-time from spin-out. UK base preferred, but a strong US base and investor network count for more than location.
• Not building, and not recently building, a company on the same substrate: agentic reasoning, knowledge graphs and hypothesis generation for drug discovery.

• Time at a frontier AI lab or a top AI-for-science company, in a role the field would recognise by name.
• A strong, transferable investor network in AI, deep tech, bio or health.
• Have scaled a company from seed to Series A and beyond.
• Commercial and business-development track record: partnerships, pilots, paying customers.
• Experience selling technical or scientific software into pharma, biotech or research institutions.

Send a CV and a short note. In the note, tell us what you think we've got wrong about the mission above.

One request, and we ask it of everyone. If your application says you raised money, be precise about five things: which fund, which round, whether that fund led it, your title on the day it closed, and what became of the company. A figure on its own tells us nothing, because it never distinguishes the money you raised from the money the company had raised while you worked there. We check.

If a founding seat isn't the right fit but the mission pulls at you, we're also open to advisory roles; say so in your note.

Deep Science Ventures (DSV) is on a mission to create a future in which both humans and the planet can thrive. We use our unique venture creation process to create, spin-out, and invest in science companies, combining available scientific knowledge and founder-type scientists into high-impact ventures. Operating across Pharmaceuticals, Climate, Agriculture, and Computation, we tackle the challenges defining these areas by taking a first-principles approach and partnering with leading institutions.