Physical Design Technical Lead, ASIC, TPU

Google’s Tensor Processing Units (TPUs) are incredibly complex, pushing the boundaries of physical design, power, and performance. In this role, you will provide technical leadership for the physical design of our next-generation AI silicon. Because of the sheer scale of our chips, our physical design leadership is highly dynamic; you will be expected to drive end-to-end execution with a scope that scales from owning highly complex, critical macro-subsystems up to overarching project-wide top-level implementation, depending on project needs.

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.

The US base salary range for this full-time position is $192,000-$278,000 + 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

• Lead the physical design implementation and strategy for high-performance silicon, with leadership scope ranging from critical, high-complexity subchips to overarching top-level execution based on project phases and team needs.
• Manage the full design cycle from RTL to GDSII, including critical sign-off closures for timing, electrical performance, and power integrity.
• Partner with internal teams (RTL, DFT, methodology, packaging) to achieve optimal power, performance, and area (PPA) results, including conducting feasibility studies for new microarchitectures and optimizing RTL runs.
• Collaborate with external EDA and IP vendors to improve flows and methodologies, while contributing to internal processes to ensure efficient and predictable execution.
• Drive execution schedules, resource planning, and risk mitigation for your area of ownership, scaling your leadership to support overall project-wide milestones.

Minimum qualifications:

• Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent practical experience.
• 10 years of experience with physical design and leading full-chip or massively intricate subchip implementation (e.g., from RTL2GDSII, including key stages like floorplanning, place and route, and timing closure) for high-speed ASICs in advanced process nodes.
• Experience in Python, Tcl, or Perl scripting.

Preferred qualifications:

• Master's degree or PhD in Electrical Engineering, Computer Engineering or Computer Science, with an emphasis on computer architecture.
• Experience with Cadence Innovus, Synopsys DP, Mentor Calibre, and StarRC, plus understanding of foundry technology files, rule decks, physical sign-off, and 2.5D/3D packaging.
• Technical leadership experience managing execution schedules, mitigating risks, and driving cross-functional collaboration with internal teams and external vendors.
• Understanding of performance, power, and area trade-offs, alongside knowledge of DFT including Scan, MBIST, and LBIST.
• Ability to navigate ambiguity, scale leadership across the physical design hierarchy, and excellent communication skills to articulate complex technical challenges to stakeholders.