Senior AI Architect

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?

Join our 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, 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 a Senior AI Architect with a good background in neural networks and hardware implementation. You will be involved with both model development, data type analysis, Machine Learning(ML)/Hardware(HW) co-design.

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.

In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.

Required Qualifications:

• 7+ years of technical engineering experience
  • OR Bachelor's degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field AND 5+ years of technical engineering experience
  • OR Master's degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field AND 3+ years of technical engineering experience
  • OR Doctorate degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field.
• 5+ years of experience developing/architecting high end CPUs and Accelerators.
• Understanding of large language models, training and inference. 
• Experience in python programming and SW engineering. 

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:

• MS/PhD in Machine learning, Computer Architecture/Systems, Electrical Engineering, High-Performance Computing or related areas.  
• Working knowledge of prevailing Large Language Models (LLM) and frameworks like Tensorflow, Pytorch is a plus.
• Good communication and collaborative mindset.
• Effective problem-solving skills and attention to details.

Hardware Engineering IC4 - The typical base pay range for this role across the U.S. is USD $117,200 - $229,200 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 $153,600 - $250,200 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 January 3, 2025

#SPARCjobs

• Develop in-house performance modeling tool for Machine Learning systems.
• Work with deployment and Software(SW) framework teams to enhance Artificial Intelligence(AI) modeling scenarios.
• Identify performance bottlenecks, optimize resource utilization, and implement improvements to enhance performance.
• Help architect large scale systems which support breakthrough performance AI workloads to shape Azure’s AI infrastructure roadmap.  
• Drive Neural Networks(NN) model/Hardware(HW) codesign.  
• Understand business critical AI workloads/applications.   
• Developing and analysing novel NN architectures.
• Other
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