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X In most instances, this position requires in-person interviews as part of the hiring process.
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, or memory subsystems.
- Experience with system architecture or GPU workload analysis and optimization.
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.
- Knowledge of GPU architecture and graphics pipelines.
- Knowledge of Vulkan, OpenGL, OpenCL, Android OS, Firmware.
- Knowledge of ARM-based system architecture concepts.
About the jobBe 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.
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 on GPU 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 bring compelling experiences leveraging GPUs to Google.
- Work with GPU Software, Android teams to optimize the software stack for GPU workloads.
