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

Deep Science Ventures • San Francisco, CA

3d • Remote

About The Position

We are building AI to predict clinical trial and drug development outcomes, and quantify the confidence in those predictions. As Co-founder & CTO, you will lead the development of a built and already-used platform, the research program to improve its predictions, and the initial technical team. The company is set to spin out of DSV in the coming months. The core problem we address is the lack of a systematic way to measure how reliably different kinds of biological evidence predict human outcomes in drug development. Our approach involves linking historical evidence, the judgments made from it, and subsequent outcomes to train models. The platform is operational and has produced a scientific result, with a public preprint available. Defining measurement, building reliable evaluations, and choosing appropriate methods are central to this role, with the next funding round dedicated to this program. A key test is predicting clinical trial outcomes and explaining the biological reasons using pre-result evidence. Safeguards against data contamination and confirmation on prospective cases are crucial, especially when using LLMs that may have encountered outcomes during training. The ultimate goal is to make therapeutic development more predictable and influence treatment selection and development processes.

Requirements

• Hands-on technical expertise and a commitment to remaining hands-on.
• Ability to engage effectively with researchers and investors.
• Leadership from the front as a founding team member with technical authority.
• Availability to commit full-time from the company's spin-out.
• Experience in evaluation and benchmark design, including defining labels, checking reliability, and designing data splits to prevent leakage.
• Strong applied statistics understanding, including calibration, confidence intervals, base rates, and limitations of small/noisy datasets.
• Breadth across modeling approaches (e.g., hierarchical and Bayesian inference, classical statistics, graph learning, probabilistic graphical models, learned calibration).
• Experience with production LLM systems, including agent orchestration, tool integrations, context management, and evaluation systems for regression detection.
• Hands-on technical leadership experience, including building systems and overseeing AI coding assistants and automated pipelines.
• Careful interpretation of results, reporting uncertainty and limitations.
• Clear technical communication skills for collaborators and investors.
• Ability to go full-time from spin-out.
• Not currently building, or recently building, a company on a similar substrate (agentic reasoning, knowledge graphs, hypothesis generation for drug discovery).

Nice To Haves

• Experience with biological or clinical data (a biology background is not required).
• Previous founding experience.
• Reviewable research, software, or open-source work.
• Experience at a frontier AI lab or a top AI-for-science company.
• Experience building evaluation or benchmarking infrastructure used by others.

Responsibilities

• Develop the platform: Take ownership of the existing system, set technical priorities, and implement improvements.
• Build the measurement program: Define prediction tasks, link decision-time evidence to subsequent outcomes, and develop/compare modeling approaches. Test predictive performance and calibration to identify system reliability.
• Prevent misleading evaluations: Address leakage, label quality, and contamination, with special care for retrospective tests involving LLMs.
• Hire the first technical team once funding is in place.
• Support fundraising by explaining the technical approach, evidence, limitations, and development plan to investors.

Benefits

• A genuine co-founder equity stake.
• A working platform and a published scientific result already in place.
• Technical authority from day one, including architecture.
• Access to DSV's global network of investors, advisors, and industrial partners.
• Access to proprietary venture-building tools, resources, and processes.
• Continuous post-spinout support including fundraising, commercial partnerships, recruitment, and team-building.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: No Education Listed