GPU Architect, Silicon

Google organizes the world's information and makes it universally accessible and useful, combining AI, Software, and Hardware to create helpful experiences.
Hardware
Mid-Level Software Engineer
In-Person
5+ years of experience
AI · Hardware

Description For GPU Architect, Silicon

Google is seeking a GPU Architect to join their innovative hardware team focused on developing custom silicon solutions for Google's direct-to-consumer products. This role is crucial in shaping the next generation of hardware experiences, particularly in the development of GPU cores for the Tensor SoC.

The position combines hardware architecture expertise with software optimization, requiring deep understanding of GPU workloads and system architecture. You'll work at the intersection of machine learning, graphics processing, and system optimization, contributing to Google's mission of creating radically helpful experiences through technology.

As a GPU Architect, you'll collaborate with multiple teams including Machine Learning, GPU Software, and Android teams to optimize GPU performance and integration within the Tensor SoC. Your work will directly impact millions of users worldwide through Google's hardware products.

The ideal candidate should have strong foundations in computer architecture, experience with GPU workload analysis, and familiarity with modern graphics APIs and ARM-based systems. This role offers the opportunity to work on cutting-edge technology while being part of Google's diverse team that pushes boundaries in hardware innovation.

Benefits include working with industry-leading experts, access to Google's vast resources and infrastructure, and the chance to influence the future of Google's hardware products. The position is based in New Taipei, Taiwan, where you'll be part of Google's growing hardware engineering presence in Asia.

Last updated 15 days ago

Responsibilities For GPU Architect, Silicon

  • Define Graphics Processing Unit (GPU) cores for the Tensor SoC based on GPU workload analysis
  • Propose architectural features/requirements for GPU to better integrate GPU with Tensor SoC to improve overall performance
  • Work with Google Machine Learning, GPU Software, Android and device teams to bring compelling experiences leveraging GPUs to Google
  • Enhance the overall Tensor SoC and software stack for GPU workloads

Requirements For GPU Architect, Silicon

Python
  • Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience
  • Experience in architecture performance analysis, tools, or simulators using C++ and Python or similar
  • Experience in using computer architecture concepts, such as pipelining, caches, virtual memory
  • Master's degree or PhD in Computer Science, Electrical Engineering preferred
  • Experience developing and analyzing workloads for GPUs preferred
  • Experience with developing optimizing compilers preferred
  • Knowledge of Vulkan, OpenGL, OpenCL, Android OS, Firmware preferred
  • Knowledge of ARM-based system architecture concepts preferred

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