Principal AI Software Architect

Microsoft•Redmond, WA

22h

About The Position

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. As Principal AI Software Architect for Microsoft MAIA accelerators within the SPARC team, you will play a pivotal role in enabling and optimizing machine learning model training workflows on our cutting-edge hardware. Your responsibilities will include bringing up and validating training processes on MAIA accelerators, collaborating with engineering and research teams to understand MAIA accelerator architecture, and enabling training recipes developed for Microsoft’s first-party accelerators. You will utilize your hands-on experience with PyTorch and at least one of Triton or CUDA to ensure efficient and scalable deployment of large models. This role is ideal for candidates who thrive in a dynamic environment and are passionate about advancing AI infrastructure and model performance on next-generation hardware platforms.

Requirements

Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, PyTorch, CUDA/Triton.
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.

Nice To Haves

Master's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor's Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
Accelerator architecture
Mapping of models to accelerators
Number formats
AI model architecture

Responsibilities

Leads by example across teams and mentors others to produce extensible, maintainable, well-tested, secure, and performant code used across products that adheres to design specifications.
Leads efforts to continuously improve code performance, testability, maintainability, effectiveness, and cost, while learning about and accounting for relevant trade-offs.
Identifies best practices and coding patterns (e.g., leveraging state-of-the-art generative artificial intelligence [GenAI], approaches to source code organization, naming conventions) and provides deep expertise in the coding and validation strategy.
Creates and applies metrics to drive code quality and stability, appropriate coding patterns, and best practices.
Identifies and anticipates blockers or unknowns during the development process, escalates them, communicates how they will impact timelines, and then leads efforts to identify and implement strategies and/or opportunities to address them.
Reviews product code and test code to ensure it meets team standards, contains the correct test coverage, and is appropriate for the product or solution area.
Brings insight to code reviews to help improve code quality, coaching and providing feedback to develop other engineers' skills.
Conducts code reviews in a timely fashion that helps accelerate the pace of development on the team. Considers diagnosability, reliability, testability, and maintainability when reviewing code, and understands when code is ready to be shared or delivered.
Applies and reviews for coding patterns, security risks, compliance issues, and best practices in code reviews, providing feedback on code to drive adherence to best practices.
Uses automated source code analysis tools that are incorporated into the build/development process.