TPU Architect, Silicon

1 Month ago • 3 Years + • Research & Development

Job Summary

Job Description

This role involves contributing to the innovation behind Google's hardware, focusing on Tensor Processing Units (TPUs). Responsibilities include building tools and dashboards for TPU power/performance analysis, analyzing machine learning workloads to propose architecture or compiler improvements, optimizing TPU micro-architecture, and collaborating with cross-functional teams to enhance end-to-end workload analysis flows. The ideal candidate will have experience with computer architecture, machine learning accelerators, and compiler optimization. This is a crucial role in shaping the next generation of hardware experiences at Google.
Must have:
  • Bachelor's degree in relevant field
  • 3+ years experience in computer architecture
  • Experience with microarchitecture, cache hierarchy, pipelining
  • Analyze ML workloads, propose architecture/compiler improvements
Good to have:
  • Master's/PhD in EE, CE, or CS
  • Experience with Machine Learning Accelerators
  • Experience in Machine Learning algorithms
  • Experience in architecting and optimizing compilers
  • Knowledge of compiler flows (e.g., TensorFlow)

Job Details


Minimum qualifications:

  • Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience.
  • 3 years of experience with computer architecture concepts, with microarchitecture, cache hierarchy, pipelining, and memory subsystems.

Preferred qualifications:

  • Master's degree or PhD in Electrical Engineering, Computer Engineering or Computer Science, with computer architecture.
  • Experience with Machine Learning Accelerators (e.g., Machine Learning Software models or accelerator architectures).
  • Experience in Machine Learning algorithms (e.g., recommendation systems, Natural Language Processing (NLP), image).
  • Experience in architecting and optimizing compilers.
  • Knowledge of compiler flows (e.g., TensorFlow).

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

  • Build up tools, flows, and dashboards for Tensor Processing Unit (TPU) power/performance analysis.
  • Analyze important Machine Learning workloads, evaluate power and performance and propose architecture or compiler improvements.
  • Analyze micro-architecture of the TPU, engage with the implementation team and propose power or performance optimization opportunities.
  • Collaborate with cross-functional teams to improve the end to end workload analysis flows, including debugging and tracing.

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