Research Scientist

My client is building autonomous AI systems designed to operate in real-world healthcare environments. Their agents function as digital clinicians and care coordinators that support patients across the full care journey, including intake, triage, navigation, post-visit follow-up, side effect monitoring, and medication adherence. These systems maintain contextual memory across interactions and can take bounded clinical actions within defined safety protocols.

Their platform is evaluated on safety, continuous improvement, and measurable impact on patient health. Agents operate autonomously within validated clinical scopes, with explicit escalation pathways and human handoff boundaries. As performance is validated across populations, those scopes expand.

They are a venture-backed company working in partnership with leading academic medical organizations. Their platform is already supporting high-volume patient interactions and is scaling rapidly.

As a Research Scientist, you will define and lead the company’s research strategy around AI agent evaluation and clinical validation. You will design rigorous studies, establish evaluation standards for safety and performance, and publish work that advances the scientific foundation of healthcare AI. This is a senior research leadership role focused on building credibility through reproducible, peer-reviewed science.

Healthcare AI research often lacks open benchmarks and strong methodology. You will help change that by setting a higher bar for transparency and rigor.

• Lead research on agent evaluation, simulation testing, and safety boundary analysis
• Publish papers and preprints at top academic venues
• Design studies linking agent behavior to clinical outcomes
• Develop frameworks to identify demographic bias and fairness risks
• Coordinate research partnerships with academic medical collaborators
• Ensure datasets and methodologies are publicly accessible and reproducible
• Manage regulatory and ethics review processes (including IRB coordination)
• Present research at conferences and represent the company in the scientific community

• PhD in machine learning, computer science, statistics, computational health, or a related field from a top institution
• Strong publication record in top-tier venues (e.g., NeurIPS, ICML, ICLR, AAAI, CHIL)
• Experience with evaluation frameworks, benchmarking, or AI safety research
• Track record of reproducible research using public datasets
• Ability to translate research insights into production improvements
• Exceptional scientific writing and communication skills
• Experience collaborating with academic institutions

• Experience at leading academic or industry AI research labs
• Publications in AI evaluation, fairness, safety, or healthcare ML
• Clinical study design experience or familiarity with IRB processes
• Background in simulation or synthetic data evaluation
• History of successful academia–industry collaboration