Member of Technical Staff - Principal AI Engineer, Health at Microsoft

London, England, United Kingdom -

Full Time

Start Date

Immediate

Expiry Date

01 Apr, 26

Salary

0.0

Posted On

01 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

AI, ML, LLM, Evaluation Frameworks, Model Training, Prototyping, Data Interpretation, Healthcare, Python, Agent Architectures, Prompt Engineering, Product Development, AI Safety, Clinical Informatics, Mentoring, Research

Industry

Software Development

Description

Overview At Microsoft AI, our Health team is on a mission to help millions of users better understand and proactively manage their health and wellbeing. We’re responsible for ensuring that Microsoft AI’s models and services are useful, trusted and safe across diverse customer health journeys. Our goal is to translate cutting-edge research—like MAI-DxO—into transformative products for millions of users across Copilot.com and Microsoft’s consumer ecosystem. About the role You'll sit between our research team and product engineering—prototyping breakthrough features, designing evaluation frameworks, and shipping safe, trusted health AI experiences. This isn't a pure research role or a pure engineering role. It's for a builder who thrives in the messy middle where frontier AI meets real users. In this role you will; Bridge research and product: Translate cutting-edge AI research into prototypes and product opportunities. Shape roadmaps with both teams to define the future of consumer health AI. Build evaluation systems: Design frameworks and infrastructure that measure model quality, safety, and utility in healthcare contexts. Create reproducible pipelines that scale across the organization. Ship prototypes rapidly: Experiment with agent architectures, prompting techniques, and new interaction paradigms. Build demos that help teams evaluate feasibility and user value. Drive decisions with data: Interpret evaluation results and present actionable recommendations to leadership, researchers, and product teams. Advocate for evidence-based product decisions. Lead through expertise: Stay current with frontier AI research and healthcare applications. Mentor teammates and shape technical direction through deep domain knowledge. Required experience/qualifications; Have extensive experience building in AI/ML with strong technical fundamentals Bring deep LLM expertise: evaluation frameworks, RLHF, model training pipelines, and agent architectures Bachelor's or Higher Degree in Computer Science, or related technical discipline AND significant Python programming experience / machine learning research. Have proven track record of building LLM agents and applications—from prompt engineering to production deployment Have shipped 0-to-1 prototypes that influenced product decisions Can translate complex technical concepts across research, engineering, and product teams Thrive in ambiguous, fast-moving environments while maintaining high quality standards Have knowledge of AI safety and responsible AI practices Have healthcare or clinical informatics background (preferred) This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Responsibilities

The role involves bridging research and product engineering by translating AI research into prototypes and product opportunities. Additionally, it includes designing evaluation systems and shipping health AI experiences.