Senior GPU System Architect, Silicon
Listed on 2026-08-07
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Engineering
Hardware Engineer, Systems Engineer
MINIMUM QUALIFICATIONS:
- Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience.
- 8 years of experience with computer architecture concepts, pipelining, ormemory subsystems.
- Experience with system architecture or GPU workload analysis and optimization.
- 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.
- Knowledge of GPU architecture and graphics pipelines.
- Knowledge of Vulkan, OpenGL, OpenCL, Android OS, Firmware.
- Knowledge of ARM-based system architecture concepts.
Be part of a team that pushes boundaries, developing custom silicon solutionsthat 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, andmore powerful. We aim to make people s lives better through technology.
Individual pay is determined by factors including job-related skills,experience, and relevant education or training.
US: $163000 - $236000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google[].
RESPONSIBILITIES:- Drive Graphics Processing Unit (GPU) architecture for the Tensor SOC based onGPU workload analysis, including high-end games, UI and ML.
- Propose system level architectural features/requirements to improve overall
SoC performance on GPU workloads. - Work with Product Management, Google Research, and device teams to bringcompelling experiences leveraging GPUs to Google.
- Work with GPU Software, Android teams to optimize the software stack for GPUworkloads.
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