ASIC Power Efficiency Engineer

About the job

As part of the TPU Power Design team, you will play a pivotal part in the power architecture and microarchitecture for our TPUs. This highly cross-functional role spans pre-silicon power modeling, to design methodology, to post-silicon data collection and analysis. Starting off by driving design power analysis, you will grow into helping define design and methodology improvements to achieve more power efficient designs. You will possess a solid understanding of power fundamentals and silicon design concepts, some exposure in performing chip power rollups, and also have an affinity for diving into adjacent disciplines in pre and post silicon.

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 $132,000-$189,000 + 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 .