TPU Hardware Design Engineer, Cloud

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Google Sunnyvale, CA, USA

X In most instances, this position requires in-person interviews as part of the hiring process.

• Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience.
• 4 years of experience in RTL design.
• Experience with digital design and microarchitecture design.
• Experience in design optimizing for performance, power, and area.

• Master's degree or PhD in Electrical Engineering, Computer Engineering or Computer Science, with an emphasis on computer architecture.
• 5 years of experience in RTL design.
• Experience with scripting languages (i.e., Python or Perl).
• Experience with Linting, Clock Domain Crossing (CDC), Reset Domain Crossing (RDC), Logic Equivalence Check (LEC).
• Experience architecting RTL solutions and with ASIC synthesis flows.
• Cross-functional engagement with Design Verification (DV) and Physical Design (PD) teams.

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 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 address challenging technical problems at the forefront of AI hardware, working in a dynamic and collaborative environment.

You will join the team designing and developing the on-chip network of Google's next-generation Tensor Processing Units (TPUs), the custom-built accelerators powering our AI and machine learning workloads in data centres. You will be responsible for the microarchitecture, design, implementation, and integration of key digital logic blocks within the TPU. This role requires close collaboration with cross-functional teams, including Verification, Physical Design, Validation, and Firmware, to deliver hardware.

You will own critical design deliverables, help with integration efforts, 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 Centre operations, systems research, and much more.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

In this role, you’ll work to shape the future of AI/ML hardware acceleration. You will…