Principal Electrical Engineer

OverviewThe Gaming Devices + Artificial Intelligence Engineering team is a team of diverse and exceptionally creative professionals who design, test and manufacture some of the best-loved gaming devices in the world. Our teams ship tens of millions of hardware products every year including the Xbox Series S, Xbox Series X, a full accessories lineup, and more. Come be part of what's next for the future of gaming! The Gaming Devices development team is seeking a Principal Electrical Engineer to drive our hardware development efforts for Artificial Intelligence across existing and future products.The Principal Electrical Engineer will lead the design and development of cutting-edge AI hardware systems. This role requires a blend of expertise in hardware engineering, machine learning, and AI algorithm development. The candidate will possess the ability to collaborate closely with our software team, System in a Chip design/architecture team, System in a Chip development partners, electrical team, test/manufacturing team, and mechanical/thermal development team, to ensure all AI experiences and goals are met or exceeded while delivering world-class end-to-end AI experience.The candidate will be versed in hardware architecture, NPUs, AI input methods, electrical engineering, System in a Chip architecture, system architecture, Firmware, Hardware (HW) accelerators, AI and Machine Learning (ML) benchmarking, Small Language Models/ Large Language Models. They will also have the ability to engage in the development of AI algorithms to enable multiple on-device experiences.ResponsibilitiesResponsibilities shall include driving the end-to-end HW AI experience for Gaming Devices, delivering hardware designs to enable AI workloads and AI input, engaging with the AI algorithms team to define and develop models and workloads for on-device and NPU compute. Working closely with multiple teams across Gaming and Microsoft to define, drive, and deliver in the end-end AI HW experience and architecture. The candidate will demonstrate a solid understanding of core engineering principles, analytical process, disciplined methodology, superior problem-solving skills, and a passion for developing technologies and products with a broad scope of impact.Experience will include significant contribution to the development of world-class consumer electronic products, System in a Chip /processors/NPUs, set-top boxes, desktop PCs, and laptop/tablet PCs, and HW AI experiences. Good technical leadership, communication skills, and willingness to tackle big challenges are necessary for this position. This candidate will own all aspects of the HW AI for future products and shall ensure good customer experience from product inception through end-of-life.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.Additional ResponsibilitiesSpecifying the hardware and architecture requirements for Artificial Intelligence experiences (including NPUs, sensor input, and others) for gaming devices while optimizing for system design constraints and cost constraints. Development and implementation of AI HW, models, and techniques to drive in-game experiences. Driving the definition of AI workloads and benchmarking. Optimizing performance, power, cost, and architecture for all aspects of AI HW related areas. Working with other engineers across disciplines to design, characterize, test and debug complex AI hardware technologies for product development. Design and develop AI hardware solutions that are scalable and efficient. Collaborate with cross-functional teams to integrate AI hardware into broader system architectures. Stay abreast of the latest AI trends and technologies to drive innovation within the company. Lead the research, testing, and implementation of machine learning algorithms and predictive models in hardware. Utilize big data computation and storage tools to create prototypes and datasets. Conduct model training, evaluation, and tuning to ensure optimal performance.

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