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.
As an RTL Design Engineer on the Tensor Processing Units (TPU) team, you will be a key contributor to the development of Google's AI accelerators. You will leverage your expertise in digital logic design, computer architecture, and RTL coding to create innovative and efficient hardware solutions. You will be responsible for the microarchitecture, design, and implementation of key digital logic blocks within the TPU. Your role requires collaborating with cross-functional teams, including Verification, Physical Design, Validation, and Firmware, to deliver hardware. You will own critical design deliverables and contribute to the continuous improvement of our design methodologies and flows.
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.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.