In this role, you’ll work to shape the future of AI/ML hardware acceleration. You will have an opportunity to drive cutting-edge TPU (Tensor Processing Unit) technology that powers Google's most demanding AI/ML applications. You’ll be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's TPU. You'll contribute to the innovation behind products loved by millions worldwide, and leverage your design and verification expertise to verify complex digital designs, with a specific focus on TPU architecture and its integration within AI/ML-driven systems. In this role, you will work on the physical implementation of Application-specific integrated circuits (ASIC) using advanced technology nodes. You will work on timing constraint development and validation for test and functional modes, and timing closure of large, complex high performance compute ASICs. You will develop static timing methodologies, margins, automation scripts, and write documentation. You will perform technical evaluations of vendors, tools, methodologies, and will provide recommendations. Additionally, you will work with architecture, logic design, and Design for testing (DFT) teams to understand and implement their requirements. The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide. We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.
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Job Type
Full-time
Career Level
Senior
Number of Employees
5,001-10,000 employees