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GPU Architect, Silicon

GPU Architect, Silicon

1 Hour ago • All levels • Research & Development

About the job

Summary

Google is seeking a GPU Architect, Silicon to contribute to the development of custom silicon solutions for their direct-to-consumer products. Responsibilities include defining GPU cores for the Tensor SoC based on workload analysis, proposing architectural features to improve performance and integration with the SoC, collaborating with various Google teams (Machine Learning, GPU Software, Android, and device teams), and enhancing the Tensor SoC and software stack for GPU workloads. The ideal candidate will have experience in architecture performance analysis, using tools and simulators with C++ and Python, and a strong understanding of computer architecture concepts like pipelining, caches, and virtual memory. Experience with GPU workload development and analysis, optimizing compilers, and knowledge of Vulkan, OpenGL, OpenCL, Android OS, and ARM-based systems are preferred.

6 skills required for this role

Test your skills to join the top 1% applicants for this job

cpp

python

open-gl

vulkan

opencl

innovation

Must have:

Bachelor's degree in relevant field
Experience in architecture performance analysis using C++/Python
Understanding of pipelining, caches, virtual memory
Define GPU cores for Tensor SoC
Propose architectural features for improved performance

Good to have:

Master's or PhD in relevant field
Experience developing/analyzing GPU workloads
Experience with optimizing compilers
Knowledge of Vulkan, OpenGL, OpenCL, Android OS, Firmware
Knowledge of ARM-based system architecture

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Minimum qualifications:

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.

Preferred qualifications:

Master's degree or PhD in Computer Science, Electrical Engineering, a related field or equivalent practical experience.
Experience developing and analyzing workloads for GPUs.
Experience with developing optimizing compilers in conjunction with hardware.
Knowledge of Vulkan, OpenGL, OpenCL, Android OS, Firmware.
Knowledge of ARM-based system architecture concepts.

About the job

Be part of a diverse 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

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.

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About The Company

Google

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A problem isn't truly solved until it's solved for all. Googlers build products that help create opportunities for everyone, whether down the street or across the globe. Bring your insight, imagination and a healthy disregard for the impossible. Bring everything that makes you unique. Together, we can build for everyone.