Manager- Applied Sciences / Machine Learning

Microsoft Microsoft · Big Tech · Redmond, WA +2 · Applied Sciences

Manager for a Core Recommendation and Content Generation team at Microsoft, focusing on LLMs and NLP to drive user engagement across various Microsoft platforms. The role involves leading a team of Applied Scientists and ML Engineers, defining technical strategy, and overseeing end-to-end execution of ML solutions.

What you'd actually do

  1. Lead and grow a team of Applied Scientists and Machine Learning Engineers, including hiring, coaching, and developing talent across Applied Science and engineering.
  2. Define technical vision and strategy for recommendation systems, Artificial Intelligence Generated Content (AIGC), and LLM-powered content generation.
  3. Drive end-to-end execution across multiple initiatives, from ideation and design to production and iteration.
  4. Oversee system architecture and scalability, ensuring robust, efficient, and high-quality ML solutions in production.
  5. Partner cross-functionally with product, engineering, and leadership teams to align on priorities and deliver customer impact.

Skills

Required

  • Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience OR Master's Degree AND 6+ years related experience OR Doctorate AND 5+ years related experience OR equivalent experience.
  • 3+ years of people management experience.

Nice to have

  • Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 12+ years related experience OR Doctorate AND 8+ years related experience 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.

What the JD emphasized

  • lead teams
  • recommendation systems
  • content generation
  • LLMs
  • large-scale ML systems
  • LLM fine-tuning
  • real-world product deployment

Other signals

  • leading teams
  • recommendation systems
  • content generation
  • LLMs
  • large-scale user engagement