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Senior GPU System Architect, Silicon

Google · Mountain View, CA, USA

External listingfull-timeRecently

About The Role

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.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $163000 - $236000 (USD) + 15% bonus target + equity + benefits

Learn more about

benefits at Google

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Minimum qualifications

  • Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience.
  • 8 years of experience with computer architecture concepts, pipelining, or memory subsystems.
  • Experience with system architecture or GPU workload analysis and optimization.

Preferred qualifications

  • Master's degree or PhD in Electrical Engineering, Computer Engineering or Computer Science, with an emphasis on computer architecture.
  • Experience developing and analyzing workloads for GPUs.
  • Knowledge of GPU architecture and graphics pipelines.
  • Knowledge of Vulkan, OpenGL, OpenCL, Android OS, Firmware.
  • Knowledge of ARM-based system architecture concepts.

Responsibilities

  • Drive Graphics Processing Unit (GPU) architecture for the Tensor SOC based on GPU workload analysis, including high-end games, UI and ML.
  • Propose system level architectural features/requirements to improve overall SoC performance on GPU workloads.
  • Work with Product Management, Google Research, and device teams to bring compelling experiences leveraging GPUs to Google.
  • Work with GPU Software, Android teams to optimize the software stack for GPU workloads.

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