RTL Design Engineer, TPU

Job description

info_outline About the job 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 join a team working on SoC-level Register-Transfer Level (RTL) design for our data center accelerators. You will design RTL Intellectual Property (IP) with the focus on management and control subsystem, also participate in developing infrastructure and methodology that form the foundation of our SoCs (i.e., clocking, reset, error handling, debug, chip management and SOC chassis etc.). You will build a global understanding of how our accelerators are built from concept to production.

This is a highly cross-functional role that will require you to coordinate and co-design with our software and system hardware counterparts. You will utilize, a background in RTL design, and the ability to lead to multi-faceted efforts involving many stakeholders. 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.

US

$163000 - $236000 (USD) + 15% bonus target + equity + benefits Learn more about benefits at Google .