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.
Our computational challenges are so big, complex and unique we can't just purchase off-the-shelf hardware, we have got to make it ourselves. Our team designs and builds the hardware, software and networking technologies that power many Google's services.
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 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: $138000 - $198000 (USD) + 15% bonus target + bonus + equity + benefits
Learn more about
benefits at Google.
Minimum qualifications:
- Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience.
- 2 years of experience in ASIC RTL design, with a focus on clocking, reset, or timing-critical RTL development.
- Experience with digital clock control circuits, including clock dividers, glitch-free muxes, and clock gating.
- Experience in SystemVerilog for creating microarchitecture specifications and synthesizable RTL.
- Experience using Python, Tcl, or Perl for automating design tasks and data analysis.
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 with high-performance ASIC design in Phase-Locked Loop, Frequency-Locked Loop, and Delay-Locked Loop integration.
- Experience implementing clock skipping, Dynamic Voltage and Frequency Scaling (DVFS), and fine-grained clock gating for low-power SoC optimization.
- Knowledge of processor design or accelerators and of high-performance and low power design techniques.
- Proficiency in Python or Perl for automating design scripts and analyzing complex clock-tree data.
- Understanding of clock distribution challenges, including jitter, skew management, and duty-cycle distortion.