Manager- Applied Sciences / Machine Learning

Microsoft•Redmond, WA

3d•$163,000 - $296,400•Hybrid

About The Position

The Microsoft Content Product team is seeking a Manager-Applied Sciences/Machine Learning (ML) to lead our Core Recommendation and Content Generation team. This is an exciting opportunity to shape the future of content services at Microsoft. Our vision is to enable billions of users worldwide to discover meaningful content and engage in conversations with friends, family, and colleagues. With nearly 1 billion monthly active users on Windows, and hundreds of millions more across Outlook, Teams, Edge, and Bing—as well as solid third-party partnerships—this role offers a unique opportunity to drive impactful, large-scale user engagement globally. 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 someone who wants to guide teams building 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. 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.

Requirements

Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience (e.g., statistics, predictive analytics, research)
OR Master's 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 Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience (e.g., statistics, predictive analytics, research)
OR equivalent experience.
3+ years of people management experience.

Nice To Haves

Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 12+ years related experience (e.g., statistics, predictive analytics, research)
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience (e.g., statistics, predictive analytics, research)
OR equivalent experience.
8+ years of industry experience in software engineering and/or machine learning, with prior experience leading teams or technical leadership roles.
Solid hands-on background in machine learning, including LLMs, NLP, or recommendation systems.
Proven track record of delivering large-scale, production-grade ML systems.
Experience leading or owning critical projects in recommendation systems or AIGC scenarios.
Proficiency in programming languages such as C/C++, C#, Java, and/or Python.
Demonstrated experience managing and growing ML teams, including performance management and career development.
Solid expertise in deep learning frameworks such as TensorFlow or PyTorch.
Experience with LLM fine-tuning, evaluation, and real-world product deployment.
Experience leading projects through full product lifecycle, from concept to launch and iteration.
Background in distributed systems and large-scale data processing.
Solid foundation in data structures, algorithms, and system design.
Experience with large-scale data analytics tools such as Spark.

Responsibilities

Lead and grow a team of Applied Scientists and Machine Learning Engineers, including hiring, coaching, and developing talent across Applied Science and engineering.
Define technical vision and strategy for recommendation systems, Artificial Intelligence Generated Content (AIGC), and LLM-powered content generation.
Drive end-to-end execution across multiple initiatives, from ideation and design to production and iteration.
Oversee system architecture and scalability, ensuring robust, efficient, and high-quality ML solutions in production.
Partner cross-functionally with product, engineering, and leadership teams to align on priorities and deliver customer impact.
Champion innovation in AIGC applications, ranking, and recommendation algorithms.
Mentor and elevate the team, fostering a culture of technical excellence, collaboration, and continuous learning.
Communicate progress, insights, and strategy to senior leadership and stakeholders.

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