Principal Applied Science Manager

Overview

The Core Recommendation Ranking team in Microsoft AI Copilot Discover Engineering Org is looking for a Principal Applied Science Manager who wants to build the next generation of recommendations using advanced AI technologies at scale.

We are responsible for content ranking and reranking to deliver most engaging and high quality recommendation results. Our content include news feeds, interest feeds, video feeds, AIGC feeds, etc. We are looking for a leader who can combine deep expertise in LLMs and NLP with proven experience in people leadership. This role is ideal for a senior technical leader who wants to guide teams to build state-of-the-art AI systems, influence product direction, and deliver scalable solutions that improve how users discover and interact with content across Microsoft platforms. You will partner closely with engineering, product, and applied science teams to design, optimize, and scale intelligent ranking systems that power personalized content experiences for millions of users.

Copilot Discover sits at the intersection of content, signals, and user intent. With nearly 1 billion monthly active users on Windows, and hundreds of millions more across Edge, Bing, Outlook and Teams, this role offers a unique opportunity to drive impactful, large-scale user engagement globally. Our ambition is to power intelligent, personalized, and trusted discovery experiences across a broad array of surfaces where Microsoft engages consumers in their journeys. If you are passionate about building high-scale, AI-driven systems that combine solid architectural rigor with meaningful user value, this is the role for you.

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

• Lead and grow a team of Applied Scientists and Machine Learning Engineers, including hiring, coaching, and developing talents across Applied Science and Engineering.
• Define technical vision and strategy for the end-to-end recommendation systems, spanning from recall, coarse ranking, fine-ranking to mixed reranking stages.
• Lead teams to build and implement next-generation recommendation systems with deep learning, LLMs, agents, and advanced recommendation techniques.
• Drive end-to-end execution across multiple initiatives, from ideation and design to production and iteration.
• Oversee system architecture and scalability, ensuring robust, efficient, extensible, and high-quality ML solutions in production.
• Partner cross-functionally with product, engineering, platform, and/or leadership teams to align on priorities and deliver customer impact.
• Mentor and elevate the team, fostering a culture of scientific rigor, innovations, engineering excellence, collaboration, and continuous learning.
• Regularly communicate team progress internally and evangelize progress and opportunities to a wider audience including leadership and stakeholders.

Qualifications

Required Qualifications:

• Bachelors Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)

• OR Masters Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics, predictive analytics, research)

• OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research).

• OR equivalent experience.

• 1+ year(s) of people management experience.

Preferred Qualifications:

• Masters Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 9+ years related experience (e.g., statistics, predictive analytics, research)

• OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)

• OR equivalent experience.

• 2+ years of people management experience. Demonstrated experience managing and growing ML teams, including performance management and career development.

• Expertise in recommendation systems, ranking models, search relevance, personalization, LLM and/or agents.

• Proficiency in modern ML frameworks (e.g., PyTorch, TensorFlow), data processing systems, and cloud‑scale infrastructure.

• Demonstrated ability to lead cross‑functional initiatives and influence technical direction across multiple teams.

• Solid communication skills with the ability to articulate complex technical concepts to diverse audiences.

• Experience with LLM‑based ranking, agentic AI, or generative AI related to recommendation or personalization.

• Publications in top‑tier ML/AI conferences (e.g., NeurIPS, ACL, AAAI, NAACL, ICML, KDD, WWW, RecSys, EMNLP, CIKM, etc).

• Solid architectural skills with experience designing and building large‑scale ML/DL systems end-to-end, distributed pipelines, and high‑throughput online services.

• Experience working through full product cycles from initial design to product delivery and iterations.

• Experience developing and designing backgrounds in multi-tiered distributed services.

• Experience with data structures, algorithms, asynchronous programming, and data processing. Knowledge and experience in large scale data analytics, such as Spark.

• Experience working with heterogeneous signals (behavioral, contextual, semantic embeddings) and multi‑objective optimization.

#MicrosoftAI

Applied Sciences M5 - The typical base pay range for this role across the U.S. is USD $142,800 - $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 - $304,200 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

https://careers.microsoft.com/us/en/us-corporate-pay

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.