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Imagine shaping the future of AI on Windows where your work directly impacts how millions of people experience intelligent computing every day. On the Windows AI Platform & Tools Team, you’ll collaborate across Microsoft and with hardware ecosystem partners to build the next generation of AI-infused experiences. You’ll be part of a team that thrives on solving complex challenges and delivering scalable solutions at the edge. As a Principal Software Engineer in our team, you will help lead the design and development of high-performance software that powers AI capabilities across Windows & Devices. You’ll architect and build code that enables developers to deploy machine learning models at scale, optimize edge execution, and guide system-level decisions around scheduling, memory orchestration, and power-aware execution and secure execution. This opportunity will accelerate your career growth through strategic leadership and technical innovation, deepen your expertise in machine learning and edge computing, and position you to influence the future of AI integration across Microsoft platforms. The role offers flexible work options, including partial remote work. 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. 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.
Job Responsibility:
Partners with appropriate stakeholders to determine user requirements for one or more complex scenarios
Provides technical leadership for the identification of dependencies and the development of design documents for a product, application, service, or platform
Leads by example and mentors others to produce extensible and maintainable code used across the company
Leverages deep subject-matter expertise of cross-product features with appropriate stakeholders (e.g., project managers) to lead multiple product's project plans, release plans, and work items
Holds accountability as a Designated Responsible Individual (DRI), mentoring engineers across products/solutions, working on call to monitor system/product/service for degradation, downtime, or interruptions
Proactively seeks new knowledge and adapts to new trends, technical solutions, and patterns that will improve the availability, reliability, efficiency, observability, and performance of products while also driving consistency in monitoring and operations at scale and shares knowledge with other engineers
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++, C#, Java, JavaScript, or Python OR equivalent experience
Proven ability to define long-term ML infrastructure strategy and drive cross-org alignment across engineering, product, and research
Hands-on experience working or building robust, ML systems with high reliability, low latency, and seamless platform integration
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role
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 have:
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 Master's Degree in Computer Science or related technical field AND 10+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience
Experience architecting ML inference pipelines for LLMs
Experience building local model integrations in system or app level components
Demonstrated mastery in ML compiler design, hardware-aware optimizations, and scalable infrastructure across heterogeneous platforms