Staff Power Management Engineer, Platforms Engineering

Google

Sunnyvale, CA, USA Posted October 26, 2026

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On-site Full-time Mid level
Job Description

Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration.
Our platforms team designs and builds the hardware, software, and networking technologies that power all of Google's services. In this role, you will design and build the systems that are the heart of the computing infrastructure. You will develop from the lowest levels of circuit design to system design and see those systems all the way through to manufacturing. Your work has the potential to shape the machinery that goes into our data centers affecting Google users. As a member of the team, you will manage projects in multiple areas. You will also monitor the performance of vendors working on projects and evaluate new technologies.
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: $188000 - $274000 (USD) + 20% bonus target + equity + benefits
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benefits at Google
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Minimum qualifications
Bachelor's degree in Electrical Engineering, Computer Engineering, Physics, a related field, or equivalent practical experience.
6 years of experience working with power chip or system power management features definition, design, implementation, integration, and testing.
3 years of experience in technical leadership.
Experience with low power design techniques, voltage/frequency scaling, xPU and system power states, power modeling, and related software/hardware.

Preferred qualifications
PhD in Electrical Engineering, Computer Engineering, Physics, a related field, or equivalent practical experience.
Experience in power system design, voltage regulation, energy storage, and conversion topologies.
Knowledge of power electronics fundamentals and various power conversion technologies for data center power delivery.
Knowledge of power converter modeling and simulation.
Knowledge of total cost of ownership modeling and simulation.

Responsibilities
Innovate and deliver initiatives for server and machine learning system power management and optimization across silicon, platform hardware, rack power, system software, and manufacturing. Design and implement power management specifications and solutions for these systems.
Develop methodologies for system power modeling and validation of power management features. Analyze trade-offs in performance, cost, reliability, and availability.
Partner with power industry leaders to guide the evaluation and adoption of technologies.
Guide cross-functional team collaboration with system architects, hardware engineers, chip designers, software/firmware teams, system qualification, and others. Deliver business justification studies.
Provide technical guidance and direction while troubleshooting system-level power management issues.

Required Skills
B2C system design manufacturing Google Cloud Platform electrical engineering testing leadership machine learning cross-functional collaboration collaboration
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