CPU Power Silicon Lab Engineer

1 Month ago • 2 Years + • Research & Development • $156,000 PA - $229,000 PA

Job Summary

Job Description

This role involves managing and upgrading Google's CPU silicon lab in Austin, TX. Responsibilities include chip validation, power measurements, performance analysis, developing test patterns, and employing data science methods for power optimization. The engineer will contribute to the innovation behind Google's products, ensuring unparalleled performance and efficiency. The position requires experience with timing, performance, and power measurements, JTAG, Python-based automation, and data analysis. Preferred qualifications include a Master's or PhD in a related field and experience with PCB-level validation and device calibration.
Must have:
  • Bachelor's degree in relevant field
  • 2 years of experience in electrical silicon lab
  • Experience with timing, performance, power measurements, JTAG
  • Python-based automation and scripting
  • Test chip validation and power analysis
Good to have:
  • Master's/PhD in Electrical Engineering/Computer Science
  • PCB-level mixed-signal validation/debug experience
  • Device calibration and trimming procedures
  • Experience with PLLs, ADCs, Current Sensors, Ring Oscillators
  • Mac/Linux OS experience
Perks:
  • Bonus
  • Equity
  • Benefits

Job Details

Minimum qualifications:

  • Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent practical experience.
  • 2 years experience working in an electrical silicon lab
  • Experience with timing, performance, power measurements, JTAG
  • Experience with Python-based automation (e.g., electrical measurement equipment, environmental chambers, etc.) and scripting (e.g., data analysis, manipulation, visualization).

Preferred qualifications:

  • Master's degree or PhD in Electrical Engineering, Computer Engineering or Computer Science, with an emphasis on computer architecture.
  • Experience with PCB-level mixed-signal validation/debug on IPs like Temp Sensor, Current Sensor, Droop Detector, ADC, Class-D amplifier, etc.
  • Experience with device calibration and trimming procedures
  • Experience with validation on PLLs, ADC, Current Sensor, Ring Oscillators, etc.
  • Experience with Mac/Linux OS.

About the job

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.

Google's mission is to organize the world's information and make it universally accessible and useful. Our team combines the best of Google AI, Software, and Hardware to create radically helpful experiences. We research, design, and develop new technologies and hardware to make computing faster, seamless, and more powerful. We aim to make people's lives better through technology.

The US base salary range for this full-time position is $156,000-$229,000 + 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 .

Responsibilities

  • Own and drive Google CPU silicon activities in a laboratory facility located in Austin. Provide daily laboratory and equipment management and upgrades as needed.
  • Test chip validation, silicon power measurements, correlation, competitive performance and power analysis.
  • Develop test patterns for power analysis, yield analysis, functionality testing and speed testing.
  • Develop data science based methods to profile workloads for performance and power to drive various activities related to power analysis and optimization.

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