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Senior CAD Engineer, Silicon, Google Cloud

Google · google.com
SunnyvaleSenior5+ yrs
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The job in short

Lead CAD methodology and tool support for chip design and verification on TPU silicon.

PythonC++Networking

Details

Found
6 d ago · posted 2026-10-23
Location as listed
Sunnyvale, CA, USA
Role
Engineering Manager
Pay (as listed)
$163,000–$236,000 a year
Source
The company’s own careers site

Full description

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 a Senior Engineer within Google's Silicon team, you will help deliver products that have a substantive impact on the technical infrastructure that powers Google. You will provide leadership to a group of hardware engineers in a fluid environment with a focus on infrastructure for chip design. You will also lead the technical projects from the concept/planning stage through execution and closure. In this role, you will help your team deliver designs that work for the first time in a number of different application areas. Leveraging your technical and leadership expertise, you will lead the chip design process improvement projects in multiple areas of expertise. 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. Responsibilities • Lead CAD methodology engineers to provide support for chip RTL or Design Verification (DV) teams; and also manage and mitigate support issues for tool flows. • Partner with chip project teams to influence and standardize methodology across functional areas and geography. • Perform or guide technical evaluations of tools for possible deployment. • Collaborate with teams across Google to identify and create opportunities for improved chip design across Google. • Participate in design reviews and track issue resolution and engage in technical and schedule trade-off discussions. Minimum qualifications: • Bachelor's degree in Electrical Engineering, Computer Science Engineering, or equivalent practical experience. • 5 years of experience working with Computer-aided design (CAD). • Experience with SystemVerilog, hardware design, automation, design verification test. • Experience with developing tools in one or more programming languages such as Python or C/C++. Preferred qualifications: • Master's degree or PhD in Electrical Engineering, Computer Engineering or Computer Science or a related field. • Experience planning and deploying new tools and flows to users. • Knowledge of the chip design process for design and verification. • Ability to present and explain novel methods to users. • Excellent automation of EDA flows using Python, AI, and related Software Engineering skills.

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