Applied AI/ML Scientist / Engineer, Health Agents
About the role
We’re looking for an Applied AI/ML Scientist to help design, validate, and operationalize health agents. This role sits at the intersection of research and product engineering, with a strong focus on experimentation, multimodal modeling, personalization, evaluation, and real-world deployment. You will work on models that turn physiological and behavioral data into safe, structured outputs that power member experience.
- Responsibilities
- Design and evaluate models for on-device health agents across wearable, CGM, EHR, lab, and behavioral data
- Translate emerging research into practical implementations for personalized health inference under mobile and edge constraints
- Define feature pipelines, training data strategy, personalization logic, and structured output schemas for agent outputs
- Build experiments and evaluation frameworks for accuracy, safety, calibration, and member-level usefulness
- Work closely with product and engineering to move promising models into production mobile workflows, including on-device inference and privacy-preserving deployment
- Contribute to model and dataset selection for key domains such as sleep, stress, and metabolic health
- RequirementsStrong applied ML / data science experience in time-series, multimodal, or physiological data
- Experience designing experiments, evaluation frameworks, and model quality metrics
- Experience with agentic LLM systems
- Ability to work across research and engineering, not just modeling in isolation
- Nice to have:Experience with on-device / edge ML, quantization, or mobile deployment
- Familiarity with wearable, CGM, EHR, or lab data
- Experience integrating model outputs into product systems built on JavaScript / TypeScript platforms
