SoC System Performance and Architecture Engineer, Silicon

1 day ago

New Taipei, Taiwan Google Full time
Minimum qualifications:
  • Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience.
  • 4 years of experience in embedded system software development, test and debugging.
  • Experience in programming (e.g., Python, or C/C++, Shell script).
  • Experience with Android/Linux environments.
Preferred qualifications:
  • Experience in power and performance analysis of CPUs, GPUs, TPUs, interconnect fabrics, or memory systems.
  • Experience with performance analysis, including software-hardware interaction and bottleneck identification (e.g., CPU, GPU, memory bound).
  • Knowledge in one or more of these areas: Quality of Service (QoS) tuning, bandwidth and latency analysis, scheduler, Dynamic Voltage and Frequency Scaling (DVFS) governor, idle governor control, thermal management, device driver.
  • Knowledge of DVFS control, thermal framework, power state control, power management ICs.
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.
Responsibilities:
  • Analyze and evaluate architectural design choices for next-generation SoCs, including central processing unit (CPU), Graphics Processing Unit (GPU), Computing cores, interconnect fabrics, and memory subsystems.
  • Conduct workload performance and power efficiency analysis to identify optimization opportunities.
  • Collaborate with hardware teams and software teams (e.g., application, framework, firmware) to drive performance improvements from concept to production.
  • Correlate pre-silicon and post-silicon results.

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