Microsoft AI Hardware/Software Co-design Engineer II 

United States, California, Mountain View 

519866354

Do 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?

Strategic Planning and Architecture(SPARC) team within Microsoft’s Azure Hardware Systems & Infrastructure (AHSI) organization and be a part of the organization 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,Teamsand 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 foranAI Hardware/Software Co-design Engineer IIto join theSystem Architectureteam focusing onarchitectureand performance aspects ofMicrosoft’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.

Minimum Qualifications:

• Bachelor’s Degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field AND 2+ years technical engineering experience

  • OR Master’s Degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field

  • OR equivalent experience.

• 2+ years of experienceworking with AI Accelerators such as GPUs or DSAs.

Other Requirements:

Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to, the following specialized security screenings:

• Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Preferred qualifications

• 4+ years related technical engineering experience
  • ORMaster's Degree in Electrical Engineering, Computer EngineeringAND 2+ years technical engineering experience
  • ORBachelor's Degree in Electrical Engineering, ComputerEngineering, AND4+ years technical engineering experience

• Deep understanding of computer architecture, SOC and SW architectures, and their performance tradeoffs.

• Working knowledge of prevailing LLM models and frameworks likeTensorflow,Pytorchis a plus

• Experience programming AI Accelerators/experience with CUDA, high performance AI libraries is a plus

• Experience in development of analysis tools written in C++ and Python.

• Knowledge of performance monitors and performance tuning.

• Proficiencyin scripting languages such as Python, Bash, or PowerShell.

• Proficient problem-solving skills and attention to detail.

• Proficient communication

• Familiarity with visualization and reporting tools likePowerBIis a plus

Hardware Engineering IC3 - The typical base pay range for this role across the U.S. is USD $98,300 - $193,200 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 $127,200 - $208,800 per year.Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

• 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 toidentifyopportunities to improve system power and performance management with a goal of improved power efficiency across the stack.

• Developin-houseperformancemodellingmethodologyand tools for Machine Learning systems.

• Benchmark andanalyzeGPU performance forbusiness criticalAI workloads

• Identifyperformance bottlenecks,optimizeresourceutilization, and implement improvements to enhance performance.

• Come up withdashboards tomaintainPerformancevisualizationand build infrastructure for improving the analysis framework

• Guide teams in designing, building, testing, and deploying changes to existing software.

• Embody our and