CPU AI Workloads and Performance Architect

2 Days ago • 5 Years + • Artificial Intelligence • $156,000 PA - $229,000 PA

Job Summary

Job Description

This role involves characterizing AI/ML workloads, identifying performance bottlenecks, and proposing CPU-focused optimization solutions. You will create instruction traces and benchmarks for performance analysis and microarchitecture exploration. Responsibilities include developing methodologies and tools for hardware-software co-design, driving cross-team collaboration on performance analysis infrastructure, and mentoring junior engineers. The work contributes to enhancing Google's products and the success of its CPU project, collaborating with Android and AI teams on application and benchmark performance analysis.
Must have:
  • Bachelor's degree in relevant field
  • 5+ years experience in high-performance CPU/AI architecture
  • Performance analysis and workload characterization
  • Proficiency in C/C++ and scripting languages
  • Create benchmarks and traces for performance evaluation
Good to have:
  • Master's/PhD in relevant field
  • Experience with Android/Linux performance tuning tools
  • Experience characterizing AI/ML or DSP workloads
  • Experience with system software components
Perks:
  • Bonus
  • Equity
  • Benefits

Job Details


Minimum qualifications:

  • Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience.
  • 5 years of experience in high-performance CPU, DSP, or AI architecture, microarchitecture.
  • Experience in performance analysis and workload characterization.
  • Experience in C/C++ and scripting languages (e.g., Python).

Preferred qualifications:

  • Master's degree or PhD in Electrical Engineering, Computer Engineering or Computer Science, with an emphasis on computer architecture.
  • Experience with Android/Linux software performance tuning tools.
  • Experience with characterizing AI/ML or DSP workloads.
  • Experience with system software components, such as Linux, drivers, and runtime.

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.

As a CPU AI workloads and performance architect, you’ll have the opportunity to collaborate with talents in Google’s Android applications and Google’s AI teams to plan and conduct application and benchmark performance analysis. Based on the infrastructures and methodologies you build, you will explore workloads and CPU design together to provide insights for hardware and software co-design. You’ll build traces and benchmarks to provide a consistent view of the workload for all stakeholders to do performance evaluation. Your work would contribute to enhancing many Google’s products and to the success of Google’s CPU project.

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

  • Characterize AI/ML workloads and identify performance bottlenecks or patterns and propose CPU-focused AI/ML workload optimization solutions.
  • Create representative instruction traces and benchmarks for performance and microarchitecture explorations.
  • Lead the development of methodologies, tools, infrastructures to enable effective hardware-software co-design.
  • Drive cross-team collaboration to design, implement and enhance performance analysis and trace collection infrastructures.
  • Mentor and guide junior engineers.

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