Job description

Overview 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 technical capabilities, cross-team collaboration, with business insight and strategy? 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 achieve 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. Join the Systems Planning and Architecture (SPARC) team within Microsoft’s Azure Hardware Systems and Infrastructure (AHSI) organization, the team behind Microsoft’s expanding Cloud Infrastructure and 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.  We are seeking a Senior AI Software Architect to join the AI Systems Architecture (ASA) group, where we define, validate, and optimize Microsoft’s next-generation AI systems across hardware, software, and cloud-scale deployment boundaries. In this role, you will drive software bring-up, performance analysis, and optimization for multiple generations of AI accelerators, working across the full stack from low-level kernels and compiler/runtime integration to distributed training, inference serving, networking, and fleet-scale system behavior. You will develop strategies that improve the correctness, efficiency, reliability, and scalability of real-world AI workloads, including deep analysis of training and inference runs to validate numerical behavior, identify bottlenecks, and guide architectural tradeoffs. You will collaborate closely with architecture, microarchitecture, compiler, runtime, networking, and systems teams to translate workload insights into practical system designs that enable efficient large-scale AI deployment. Responsibilities RESPONSIBILITIES: • Lead end-to-end software architecture and performance optimization for AI accelerator platforms. • Prototype and validate software capabilities across kernels, compiler and runtime layers, distributed training and inference frameworks, and serving infrastructure. • Analyze workload behavior at scale to identify performance bottlenecks, numerical correctness issues, and system-level efficiency opportunities. • Use workload insights to guide hardware-software co-design decisions across architecture, silicon, systems software, networking, and product teams. • Define requirements, evaluate tradeoffs, and deliver practical solutions for production-scale AI systems. Qualifications QUALIFICATIONS: Required Qualifications • Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. 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 • PhD in Computer Science,Computer Architecture, Electrical Engineering, Machine Learning, High-Performance Computing, or a related field OR Master's Degree in Computer Science, Electrical Engineering, Computer Engineering, or related field AND 3+ years technical engineering experience OR Bachelor's Degree in Computer Science, Electrical Engineering, Computer Engineering, or related field AND 5+ years technical engineering experience OR equivalent experience. • Experience designing, building, or optimizing systems software for AI, machine learning, high-performance computing, or distributed systems. • Experience analyzing large-scale AI training runs, including loss curves, convergence behavior, gradient flow, activation statistics, and numerical stability. • Experience debugging training correctness issues such as gradient divergence, NaNs/Infs, optimizer behavior, mixed-precision instability, distributed synchronization bugs, or hardware/software numerical differences. Hardware Engineering IC6 - The typical base pay range for this role across the U.S. is USD $165,600 - $296,400 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 $220,800 - $331,200 per year. Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: careers.microsoft.com This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Requirements

Must-haves

Lead end-to-end software architecture and performance optimization for AI accelerator platforms.
Prototype and validate software capabilities across kernels, compiler and runtime layers, distributed training and inference frameworks, and serving infrastructure.
Analyze workload behavior at scale to identify performance bottlenecks, numerical correctness issues, and system-level efficiency opportunities.
Use workload insights to guide hardware-software co-design decisions across architecture, silicon, systems software, networking, and product teams.
Define requirements, evaluate tradeoffs, and deliver practical solutions for production-scale AI systems.
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.
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Nice-to-haves

Experience designing, building, or optimizing systems software for AI, machine learning, high-performance computing, or distributed systems.
Experience analyzing large-scale AI training runs, including loss curves, convergence behavior, gradient flow, activation statistics, and numerical stability.
Experience debugging training correctness issues such as gradient divergence, NaNs/Infs, optimizer behavior, mixed-precision instability, distributed synchronization bugs, or hardware/software numerical differences.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

Application prep

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Keywords to mirror

azureaijavajavascriptpythonmachine learning

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