TPU Hardware Design Engineer, Cloud

Socket.dev; Sunnyvale (CA); On-site; USD 138,000 - 197,000; Full time

Benefits offered by this job

Bonus target

Equity

Benefits

Job summary

Google in Sunnyvale seeks an RTL Design Engineer to shape the TPU microarchitecture and deliver high-quality SystemVerilog RTL for AI/ML accelerators. You will drive design decisions that balance performance, power, and area while collaborating with Verification and Physical Design to meet timing and manufacturability requirements.

You’ll own critical design deliverables, partner with DV and PD teams across the TPU ecosystem, and contribute to post-silicon validation and integration.

Qualifications

• 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.

Responsibilities

• Define TPU microarchitecture and develop high-quality, performant, and power-efficient SystemVerilog RTL code for complex digital designs.
• Partner with Verification teams to develop test plans, debug RTL, and ensure functional correctness, alongside supporting post-silicon validation efforts.
• Collaborate closely with the Physical Design team to successfully meet stringent timing, area, power, and manufacturability requirements.
• Work seamlessly with internal Partner teams to support and drive critical design integration efforts across the ecosystem.

Skills

RTL design

digital design

microarchitecture design

performance optimization

power optimization

area optimization

Education

Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or related field

Tools

Python

Perl

Linting

CDC

RDC

LEC

ASIC synthesis flows

Job description

MINIMUM QUALIFICATIONS

• 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.

PREFERRED QUALIFICATIONS

• 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.

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 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 centers. 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 team behind Google's groundbreaking innovations, empowering the development of our 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: $138000 - $197000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google [https://www.google.com/about/careers/applications/benefits/].

RESPONSIBILITIES

• Define TPU microarchitecture and develop high-quality, performant, and power-efficient SystemVerilog RTL code for complex digital designs.
• Partner with Verification teams to develop test plans, debug RTL, and ensure functional correctness, alongside supporting post-silicon validation efforts.
• Collaborate closely with the Physical Design team to successfully meet stringent timing, area, power, and manufacturability requirements.
• Work seamlessly with internal Partner teams to support and drive critical design integration efforts across the ecosystem.