SoC Design Engineer, Tensor Processing Unit, Cloud

Minimum qualifications:

• Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience.
• 2 years of experience architecting RTL solutions employing software based construction, instantiation, customization or generation of RTL.
• Experience with industry-standard EDA tools for simulation, synthesis, and power analysis.

Preferred qualifications:

• Master's degree or PhD in Electrical Engineering, Computer Engineering or Computer Science, with an emphasis on computer architecture.
• Experience with scripting languages (i.e. Tcl, Python or Perl).
• Experience architecting RTL solutions employing software based construction, instantiation, customization and generation of RTL.
• Experience with SOC implementation standards and interfaces (i.e. AXI).
• Experience with CDC, RDC, RTL Linting and LEC.
• Understanding of digital design fundamentals, including synchronous and asynchronous logic, state machines, and bus protocols.

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 RTL design for data center accelerators. You will work on top-level RTL, architecture, design and implementation of global communication busses, and integration of complex ASIC designs, as this is a highly cross-functional and central role that will require interactions with numerous ASIC development teams. You will own deliverables to the cross-functional teams (i.e. Physical Design, Verification, Validation, Firmware...) at various project milestones. You will also be directly involved in defining and creating methodologies that enable a highly efficient design environment for all ASIC engineers.

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 channel 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.

The US base salary range for this full-time position is $138,000-$198,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities:

• Define and document the microarchitecture for digital designs within the TPU.
• Develop high-quality, performant, and power-efficient Register Transfer Level (RTL) code, primarily in SystemVerilog.
• Partner with the Verification team to develop test plans, debug RTL, and ensure functional correctness.
• Work closely with the Physical Design team to meet timing, area, power, and manufacturability requirements.
• Contribute to the development and enhancement of design tools, flows, and methodologies.