Principal Applied Scientist

Copilot Discover helps hundreds of millions of people be informed, entertained, and inspired by surfacing highly relevant, trustworthy, and delightful content across Microsoft surfaces. We’re building the next generation of AI‑powered content recommendation systems—spanning text, images, audio, and video—to curate the right content at the right moment for each user while upholding safety and integrity.

As a Principal Applied Scientist, you’ll lead the science behind Discover’s ranking, user understanding, and content understanding stack, combining LLMs, multimodal models, and large‑scale recommender systems to drive measurable gains in engagement, satisfaction, and trust. You will set technical direction, mentor a high‑caliber science cohort, and partner closely with engineering, PM, UXR, and policy to ship end‑to‑end outcomes. You will contribute to the development of the next generation of MSN that is adopting the latest generative AI techniques.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50- mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.

Responsibilities

• Advance the recommendation & ranking stack. Architect and productionize large‑scale DNN/LLM‑enhanced recommenders (representation learning, sequence modeling, retrieval/ranking, slate optimization), balancing user satisfaction, content quality, and business goals.

• Deepen user & content understanding. Gather and analyze user signals from diverse sources to gain a thorough understanding of user behaviors and utilize ML/AI techniques to interpret and predict user needs and preferences. Design and build models that assess content quality and utility aspects to ensure product safety and drive sustainable user engagement.

• Scale E2E ML/AI systems. Collaborate with engineering on data contracts, feature stores, distributed training/inference, and automated rollout/rollback; drive architectural investments that increase agility and reliability of Discover’s AI platform.