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Performance Co-Design Engineer, Google Cloud TPU

Google · United States · On-site

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About Google

Learn more about Google. Explore our innovative AI products and services, and how we. Backed by Kleiner Perkins.

About the role

In this role, you’ll work to shape the future of AI/ML hardware acceleration. You will have an opportunity to drive cutting-edge TPU (Tensor Processing Unit) technology that powers Google's most demanding AI/ML applications. You’ll be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's TPU.

What they're looking for

  • Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent practical experience
  • 10 years of experience in computer architecture, chip architecture, or hardware-software co-design
  • Experience developing systems for performance modeling, simulation, or system analysis
More about this role
  • Drive the definition and optimization of the hardware/software stack to enable performant training and serving of large ML models.
  • Collaborate with research and modeling teams to innovate on model architectures, focusing on scaling, quality, and their direct impact on hardware performance.
  • Lead the development of configurable architectural simulators and cycle-accurate performance models to quantify microarchitectural optimizations and evaluate architectural decisions.
  • Conduct system-level performance analysis across highly distributed ML systems, innovating new methodologies to balance compute, memory bandwidth, and inter-chip network requirements.
  • Engage with partners across hardware design, compiler development, and ML research to transition architectural innovations from concept to production.
  • Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent practical experience.
  • 10 years of experience in computer architecture, chip architecture, or hardware-software co-design.
  • Experience developing systems for performance modeling, simulation, or system analysis.
  • Master's degree or PhD in Electrical...

Read the full posting on Google's site ↗

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