GPU Architect, Silicon

仕事内容

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Minimum qualifications:

• Master’s degree in Electrical Engineering, Computer Science, 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.
  
  

Preferred qualifications:

• PhD in Electrical Engineering or Computer Science.
• Experience developing and analyzing workloads for GPUs.
• Experience with developing optimizing compilers in conjunction with hardware.
• Knowledge of GPU software and/or hardware pipeline architecture.
• Knowledge of Vulkan, OpenGL, OpenCL, Android OS, Firmware.
• Knowledge of ARM-based system architecture concepts.
  
  

About The Job

Google engineers develop the next-generation technologies that change how users connect, explore, and interact with information and one another. As a member of an extraordinarily creative, motivated and talented team, you develop new products that are used by millions of people. We need our engineers to be versatile and passionate to take on new problems as we continue to push technology forward. If you get excited about building new things and working across discipline lines, then our team might be your next career step.

In this role, you will architect/configure the main Graphics Processing Unit (GPU) cluster on ASIC products. You will collaborate with software and hardware architects to optimize gaming, imaging and other relevant workloads running on the GPU. You will project performance/power on key workloads to assess the engagement of the design as part of the overall ASIC definition.

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

• Define configuration of Graphics Processing Unit cores for ASICs based on GPU workload analysis.
• Propose architectural features/requirements for GPU to integrate GPU with ASIC to improve overall performance.
• Work with Google Machine Learning, software, and device teams to bring compelling experiences leveraging GPUs to Google.
• Optimize the overall ASIC and software stack for GPU workloads.
  
  

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google’s EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .