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 Application-Specific Integrated Circuit (ASIC) Physical Design Lead on the chip implementation team, you will work on the physical implementation of ASICs in advanced technology nodes. You will drive teams towards common execution goals by setting priorities and creating detailed task and check lists, tracking execution progress and status, course correcting as needed, escalating and resolving critical issues. You will be ultimately responsible to deliver physical designs at the floor plan block level, subsystem level, and chip level on schedule and to required quality levels. You'll work on and lead teams performing physical design including place and route, EMIR, static timing, and physical verification. In addition, you will go beyond automated flow execution and use industry standard Exploratory Data Analysis (EDA) and Confirmatory Data Analysis (CDA) tools to perform custom design work, provide customized solutions to specific problems, and enhance Power Performance Area (PPA).
The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.
We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud's Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.
The US base salary range for this full-time position is $183,000-$271,000 + 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.
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