Principal Applied Scientist, Experimentation Platform - Coreai

Microsoft Microsoft · Big Tech · Redmond, WA +4 · Applied Sciences

This role focuses on building and scaling an experimentation platform for AI products, enabling teams to evaluate, refine, and safely deploy new AI innovations. It involves pushing the envelope on online experimentation methodology and agent evaluations, collaborating with various engineering and science teams, and translating applied research into production-quality features.

What you'd actually do

  1. Push the envelope on online experimentation methodology and agent evaluations, advancing the state-of-the-art by connecting product development needs, latest science techniques and platform opportunities
  2. Contribute to one of the highest-scale experimentation platforms on the planet
  3. Collaborate closely with backend engineers, data scientists, site reliability engineers (SREs), and product managers to gather requirements, iterate on features, and deliver seamless, end-to-end user experiences.
  4. Collaborate closely with designers, UI-experts, science leaders and engineers to ensure clear, actionable dashboards and visualizations that empower users to make trustworthy science-informed decisions.
  5. Collaborate with and bridge the gaps between researchers (e.g., across CoreAI, Microsoft Research [MSR] and open source communities) to translate applied research into differentiated, production-quality features

Skills

Required

  • Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience OR equivalent experience
  • Ability to meet Microsoft, customer and/or government security screening requirements

Nice to have

  • Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience
  • Experience with Agent based architectures, frameworks and technologies (such as MCP, A2A protocol, or Azure AI Foundry)
  • 3+ years of experience developing and deploying products or systems at multiple points in the product cycle from ideation to shipping as part of a product team.
  • Proven track record designing and scaling online experimentation platforms that support high‑velocity A/B and multivariate testing across complex, multi‑team product ecosystems, including governance, guardrails, and causal inference best practices.
  • Demonstrated thought leadership in product measurement strategy, with the ability to define north‑star metrics, architect measurement frameworks, and influence senior product and engineering leaders on how to interpret ambiguous or noisy data at scale.
  • 5+ years experience creating publications (e.g., patents, libraries, peer-reviewed academic papers).

What the JD emphasized

  • Push the envelope on online experimentation methodology and agent evaluations
  • agent evaluations
  • experimentation methodology
  • production-quality features
  • scaling online experimentation platforms
  • governance, guardrails, and causal inference best practices
  • measurement strategy
  • interpret ambiguous or noisy data at scale

Other signals

  • experimentation platform
  • AI ecosystem
  • agent evaluations
  • high-scale experimentation