Silicon Engineer

2 Months ago • 3-7 Years • Research Development

Job Summary

Job Description

As a Silicon Engineer at Google, you'll be a key contributor to CPU subsystem architecture and microarchitecture definitions. You'll collaborate with performance and software teams for workload analysis, debugging, and performance projection. Leveraging your CPU expertise, you'll work with other teams on CPU configuration, architecture features, and PPA (Performance, Power, Area) trade-off analysis. Responsibilities include defining architectural aspects of the CPU subsystem (power control, fabric structure, debug, etc.), participating in PPA trade-off analysis, assessing performance analysis infrastructure, defining low-power schemes, and defining future roadmap features and performance requirements.
Must have:
  • Bachelor's degree in relevant field
  • 3+ years low power RTL and physical design experience
  • Scripting language experience (Python, Perl)
  • CPU subsystem architecture definition
  • PPA trade-off analysis
Good to have:
  • Master's/PhD in relevant field
  • ARM ISA, PPA, design, microarchitecture experience
  • CPU application experience for mobile/wearable products
  • Experience with AI engines, branch predictors, IFU, LSU, advanced prefetching

Job Details

Minimum qualifications:

  • Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent practical experience.
  • 3 years of experience with low power RTL and physical design techniques.
  • Experience with scripting languages (e.g., Python, Perl).

Preferred qualifications:

  • Master’s degree/PhD in Electrical Engineering, Computer Engineering, or Computer Science, emphasizing on computer architecture.
  • 3 years of experience in ARM ISA, PPA, design and microarchitecture.
  • 1 year of experience in CPU applications for mobile and wearable products.
  • Experience on advanced CPU techniques such as AI engines, branch predictors, IFU, LSU and advanced prefetching algorithms.

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.

As a Silicon Engineer, you will be the key contributor to the CPU subsystem architecture and microarchitecture definitions. You will collaborate with system performance and software teams to plan and conduct workload performance analysis, debug performance bottlenecks and project performance at various design phases. Leveraging your CPU-specific knowledge and expertise, you will be working with engineers in power, thermal, security, physical design and other subsystem teams on the CPU subsystem configuration, architecture and microarchitecture features, and PPA (Performance, Power, Area) trade-off analysis.
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

  • Define various architectural aspects of CPU subsystem including but not limited to, active and idle power control, fabric structure, debug, analytics and other sub system components.
  • Participate in Performance, Power, Area (PPA) trade-off analysis for architecture and microarchitecture features. Communicate analysis results in both qualitative and quantitative fashion to support major decisions.
  • Assess performance analysis infrastructure, which includes preparing workloads, developing performance models, and conducting performance and workload analysis.
  • Define next generation low power schemes.
  • Define future roadmap features and performance requirements.

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