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.
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Mid-Level Software Engineer
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AI · Hardware

Description For GPU Architect, Silicon

Google is seeking a GPU Architect to join their Silicon team, focusing on developing custom silicon solutions for Google's direct-to-consumer products. This role combines hardware architecture expertise with software optimization, working specifically on GPU cores for the Tensor SoC. The position requires deep understanding of computer architecture concepts and GPU workloads, with opportunities to work alongside Machine Learning, GPU Software, and Android teams.

The ideal candidate will have strong background in computer architecture, experience with GPU workload analysis, and familiarity with various graphics APIs and ARM-based systems. They will be responsible for defining GPU cores, proposing architectural improvements, and enhancing the overall Tensor SoC performance.

This role offers the unique opportunity to shape the future of Google's hardware experiences, working on technology that impacts millions of users worldwide. The position combines technical depth in GPU architecture with broad exposure to Google's AI and software stack, making it an exciting opportunity for someone passionate about hardware-software integration and performance optimization.

Working at Google provides exposure to cutting-edge technology and the chance to work with diverse, talented teams. The company offers a supportive environment for people with disabilities and maintains a strong commitment to equal opportunity employment. This role is based in New Taipei City, Taiwan, putting you at the heart of Google's hardware innovation efforts.

Last updated 2 months 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 engaging 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, a related field or equivalent practical experience (preferred)
  • Experience developing and analyzing workloads for GPUs (preferred)
  • Experience with developing optimizing compilers in conjunction with hardware (preferred)
  • Knowledge of Vulkan, OpenGL, OpenCL, Android OS, Firmware (preferred)
  • Knowledge of ARM-based system architecture concepts (preferred)

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