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Minimum qualifications:
- Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience.
- 5 years of experience with computer architecture concepts, including microarchitecture, cache hierarchy, pipelining, and memory subsystems.
- Experience with system architecture or GPU workload analysis.
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.
- 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 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
- Drive GPU architecture for the Tensor SOC based on GPU workload analysis, including games, User Interface, and Machine Learning.
- 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 experiences leveraging GPUs to Google.
- Work with GPU Software, Android teams to optimize the software stack for GPU workloads.
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