New 
AI Hardware/Software Co-design Engineer II
 Microsoft | |
 United States, California, Mountain View | |
 Jan 22, 2025 | |
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OverviewDo you want to be at the forefront of innovating the latest hardware designs to propel Microsoft's cloud growth? Are you seeking a unique career opportunity that combines both technical capabilities, cross team collaboration, with business insight and strategy? Join our Strategic Planning and Architecture (SPARC)team within Microsoft's Azure Hardware Systems & Infrastructure(AHSI)organization and be a part of theorganization behind Microsoft's expanding Cloud Infrastructure and responsible for powering Microsoft's "Intelligent Cloud" mission. Microsoft delivers more than 200 online services to more than one billion individuals worldwide and AHSI is the team behind our expanding cloud infrastructure. We deliver the core infrastructure and foundational technologies for Microsoft's cloud businesses including Microsoft Azure, Bing, MSN, Office 365, OneDrive, Skype, Teams and Xbox Live. The SPARC organization manages Azure's hardware roadmap from architecture concept through production for all of Microsoft's current and future on-line services. We are looking for an AI Hardware/Software Co-design Engineer II to join the System Architecture team focusing on architecture and performance aspects of Microsoft's Azure hardware systems deployed in various data centres across the globe. 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.
Responsibilities Work with business, architecture, and design teams to understand performance requirements and collaborate across functional teams to meet these needs in technology development planning and path finding. Work with platform, firmware, and software teams across Microsoft to identify opportunities to improve system power and performance management with a goal of improved power efficiency across the stack. Develop in-house performance modelling methodology and tools for Machine Learning systems. Benchmark and analyze GPU performance for business critical AI workloads Identify performance bottlenecks, optimize resource utilization, and implement improvements to enhance performance. Come up with dashboards to maintain Performance visualization and build infrastructure for improving the analysis framework Guide teams in designing, building, testing, and deploying changes to existing software. Embody our culture and values. | |