At Microsoft, we operate the largest collaboration services in the world with 100s of millions of consumer/enterprise mailboxes, documents, and conversations. It represents the world’s largest platform of human collaboration for personal, business, and educational use. Within our Microsoft wide Systems Innovation initiative, we are working on advancing efficiency across AI systems, where we look at novel designs and optimizations across AI stacks: hardware, cloud infrastructure, AI framework s , and models. We believe that e nabling cross-layer optimization is the key to achieve a step-function improvement in AI efficiency .
We are an Applied Research team driving mid- and long-term product innovations. We closely collaborate with multiple research teams and product groups across the globe who bring a multitude of technical expertise in cloud systems, machine learning and software engineering. We communicate our research both internally and externally through academic publications, open-source releases, blog posts, patents, and industry conferences. Further, we also collaborate with academic and industry partners to advance the state of the art.
We are looking for a Principal Product Manager to shape our long-term research strategy and increase product impact. You will work closely with research and engineering teams across Microsoft to identify research opportunities, drive organizational alignment, and communication our cutting-edge research agenda both internally and externally. You will play a critical role in shaping our cross-disciplinary research strategy spanning several critical technology areas such as Large Language Models ( LLM) e fficiency, hybrid cloud/edge inferencing, AI infrastructure optimization, and novel silicon/ hardware architecture
Qualifications:
Required/Minimum Qualifications
- Bachelor’s Degree AND 8+ years experience in product/program management/research
- OR equivalent experience.
- Prior experience working on research collaborations or new product incubations.
- Experience managing cross-functional and/or cross-team projects.
Additional or Preferred Qualifications
- PhD in computer science (or related field)
- 5+ years’ experience managing cross-functional and/or cross-team projects.
- Be able to work in a cross-functional and multi-disciplinary setting across research and product.
- Interest in applied research and open-ended problems.
- Knowledge and understanding of various optimization s of deep learning model architectures and algorithms for CPU/GPU, mobile, and other types of specialized hardware .
- Understanding of open problems in AI efficienc y and/or experience with productizing AI/ML based solutions.
Product Management IC5 – The typical base pay range for this role across the U.S. is USD $133,600 – $256,800 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 $173,200 – $282,200 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
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form .
Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.
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Responsibilities:
- Partner with research and product teams across multiple disciplines to establish technology transfer pipeline.
- Engage with engineering teams to identify challenges and opportunities for efficiency in AI training and inferencing , with a focus on LLM .
- Drive clarity to research goals and help to shape a long-term research strategy.
- Advocate our research agenda and accomplishments to organizational and company leadership.
- Drive internal and external outreach activities via conferences, workshops, newsletters, etc. which will help evangelize and increase visibility of the research efforts.