Location: San Francisco, CA

Work Model: Onsite

Industry: Artificial Intelligence / Data

Compensation: $130K-$150K base, target cash compensation around $300K (profit share plus equity)

About the Company

Our partner is a venture-backed AI data company that works directly with frontier AI research labs. They design and deliver the expert-generated datasets used to train foundation models, and they operate at the point where domain expertise meets model development.

The Opportunity

This is a healthcare-specialized operations lead role. You will manage teams of expert contributors across healthcare, medicine and biopharma, and you will work directly with client research teams to design datasets that shape how foundation models reason about medicine.

The work sits between clinical judgment and machine learning. You need enough domain depth to evaluate whether medical content is correct and whether a task is well specified, enough leadership ability to run expert teams at pace, and enough technical comfort to work fluently with data and AI tooling. The environment is fast-moving and lightly directed; the people who do well here define their own scope.

Responsibilities

• Manage expert teams across healthcare, medicine and biopharma
• Work directly with client research teams to scope and design datasets
• Own quality standards for medical and clinical content
• Translate ambiguous research goals into executable project plans
• Use data tooling and AI systems to automate and scale delivery
• Communicate progress, tradeoffs and risks to technical stakeholders

Requirements

• 3+ years of experience in healthcare, medical research, health technology, biopharma or a comparably selective healthcare or medicine environment
• Background in medicine, clinical practice, biomedical research, healthcare operations or an adjacent discipline
• Strong understanding of healthcare data, systems, clinical workflows or medical research
• Demonstrated leadership experience
• High agency and the ability to execute with minimal direction in ambiguous conditions
• Excellent written and verbal communication
• Comfort working with data, technical systems and AI tools