Staff AI Scientist

Role overview

A staff-level AI scientist is needed to own end-to-end development of core intelligent capabilities within a Health Intelligence team that blends classical machine learning with modern generative AI. The role spans research, modeling, evaluation, and production deployment, focusing on personalization and recommendation systems that translate health signals into safe, relevant, and personalized member experiences.

Responsibilities

- Research, build, evaluate, and ship reusable intelligence systems, taking ownership from scientific signal through product integration, launch, and iteration. - Set the technical agenda for personalization strategy, influencing roadmap and direction across partner teams. - Design measurement frameworks and lightweight offline evaluation and shadow-mode infrastructure that enable fast iteration without long A/B cycles. - Support causal and counterfactual modeling to distinguish real outcome effects from confounding variables, and design experiments that measure genuine impact. - Provide technical mentorship to scientists and engineers, shaping team norms around experimentation, evaluation, and personalization quality. - Partner with engineering, science, product, and design to integrate personalization into the broader member experience, communicating trade-offs and uncertainty clearly across US and EU teams.

Requirements

- 8+ years of experience in applied AI, AI research, and backend engineering, with a graduate degree (MS or PhD) in a quantitative field strongly preferred. - Deep experience with AI and LLM-backed products and evaluation workflows, including LLM-as-judge, rubric-based evaluation, and safety or red-teaming practices, shipped to production. - Deep backend engineering experience, including building systems that serve millions of users. - Hands-on experience across retrieval, ranking, and recommendation system design, including collaborative filtering, embedding-based approaches, or graph networks. - Comfort working closely with server and app engineers on model serving, pipeline architecture, and deployment infrastructure. - Strong proficiency in Python, modern data tooling, and the ability to explain complex systems and uncertainty to technical and non-technical audiences.

Nice to have

- Experience designing personalization for consumer behavior change or health outcomes, including engagement and longitudinal impact. - Familiarity with health, wearables, or digital therapeutics domains and interest in how personalization compounds over time. - Comfort working across time zones with distributed, cross-functional teams.

Benefits and work setup

- Competitive salary with market-based pay ranges that vary by US location tier, ranging from roughly $199,000 - $267,950 annually, plus equity. - Health, dental, vision insurance, mental health resources, a wearable device of their own, and family discounts. - 20 days of paid time off, 13 paid holidays, and 8 days of flexible wellness time off, alongside paid sick leave and parental leave. - US Remote role.