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Unlearn.AI is transforming clinical development by using AI and digital twins to make clinical trials faster and more robust. The company partners with biopharmaceutical companies to redesign how trials are planned, run, and analyzed. Founded in 2017 by machine learning scientists and headquartered in San Francisco, Unlearn has raised $50M in Series C funding from top-tier investors including Altimeter, Insight Partners, and DCVC.
You will own the data products that power Unlearn's AI models—the pipelines, datasets, and tooling that transform raw clinical trial data into training-ready inputs for the scientific team. This is a hands-on internal platform product role where you'll work directly with the engineers building infrastructure and the teams building and deploying models for customers.
Your day-to-day involves understanding how internal teams actually work, deciding what gets built next, and ensuring it ships and gets adopted. You'll spend significant time alongside engineers and data scientists, exploring problems in the data itself rather than relying solely on backlogs. You'll own this area end-to-end, partnering closely with the Head of Product on overall direction and with engineering and scientific leads whose teams depend on your work.
In your first 90 days, you'll map how data flows from raw clinical trials to model inputs, identify friction points, and deliver a prioritized roadmap. You'll ship measurable improvements that speed up model delivery (success measured in faster model development, not feature count), and establish a prioritization rhythm that partner teams trust.
Key responsibilities include: owning the roadmap for your data platform area from problem definition through delivery and adoption; developing deep understanding of how scientific and engineering teams build models and translating that into prioritized work; writing clear problem statements and requirements; partnering with engineering leads on technical design decisions; defining and measuring success for your area; running planning and prioritization rhythms; and working directly with data to answer questions about usage, quality, and bottlenecks.
REQUIREMENTS:
- At least 3 years as a product manager on technical products, with meaningful experience on data platforms, developer tools, or internal infrastructure
- Track record of owning a product area end-to-end and shipping products with real adoption (not just delivered features)
- Real technical depth: ability to read schemas, write queries, reason about pipeline architecture, and credibly discuss design tradeoffs with engineers
- Comfort working with messy, high-volume, structured data; habit of exploring data yourself before forming views
- Clear written thinking; ability to lay out problems, options, and recommendations in documents that technical audiences take seriously
- Judgment to work independently within a defined scope and recognize when decisions require collaboration
- AI-native mindset; ability to incorporate AI into daily workflow
- Owner's mindset; willingness to tackle hard problems
- Passion for the mission of transforming clinical development
NICE TO HAVE:
- Experience with clinical trial data or clinical data standards
- Background in biopharma industry or clinical development
- Experience supporting machine learning teams, particularly on data side of model development
- Experience turning internal tooling into sellable products
- Experience with Databricks
