Microsoft Principal Researcher 

United States, Washington 

543133157

Generative AI is revolutionizing how we create, share, work with, and consume content. At Microsoft, we run the biggest platform for collaboration and productivity in the world with hundreds of millions of consumer/enterprise users. Tacklingthese experiences at scale.

are workingefficiency across AI systems, where we look at novel designs and optimizations across AI stacks:models, AI frameworks, cloudinfrastructure, and. We believe that enabling cross-layer optimization is the key to achieve a step-function improvement in AI efficiencyto provide generative AI experiences to more users globally.

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 artand target material product impact that will affect 100s of millions of customers.

Researcher tocross-stack optimizations to deliversignificant efficiency gains forLarge Language Model / Generative AI.experience inmodel architectures,LLM frameworks,serving infrastructure and/orarchitecture optimisation.with an interest to work at the intersection of LLMs and systems research,well as the motivation and ambition to apply this research in a meaningful real-world setting.We are looking for a Principal Researcher with an inter-disciplinary background in AI, Distributed Systems and Privacy research including efficient training and inference of Large Language Models (LLMs), reliability of web scale cloud workloads and privacy mitigations in machine learning. You will be one of the key architects behind the vision and strategy of our research team with 40+ world class researchers. You will help drive cross-organizational execution to deliver company and academic impact.

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.

Required/Minimum Qualifications

• Doctorate in relevant field AND 3+ years related-research experience
  • OR equivalent experience.
• Research experience and publications in top conferences/journalsin at least one of the following areas:natural language processing,statistics, machine learning,and optimization.

Additional or Preferred Qualifications

• PhD in Statistics, Computer Science, Engineering, Mathematics, Physics, or related field AND5+ years related experience (e.g., statistics predictive analytics, research)
  • OR equivalent experience.
• Solid knowledge of state-of-the-artLarge Language Models (LLMs),serving infrastructure,andtheirapplication in complex systems.
• Hands on experience in improving thedesign andefficiency of generative AIsystemsand relatedframeworks.
• Ability to work independently and in a team, take initiative and lead engagements as required.

Research Sciences IC5 - The typical base pay range for this role across the U.S. is USD $137,600 - $267,000 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 $180,400 - $294,000 per year.Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

Microsoft will accept applications for the role until Aug 3, 2024.

• Conduct novel research to advance the state-of-the-artofefficiencyoptimizations across AI stacks: models, AI frameworks, cloud infrastructure, and hardware.
• Work with a small group of fellow researchersand product engineering teams to executeonpracticalinnovationfor real-world impact.
• Drivethe end-to-end research agenda from establishing the problem definition to building algorithms and models, and act as a mentor forteam members.
• Publish and contribute to top scientific conferences and journals.

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