Senior GPU System Architect, Silicon

In most instances, this position requires in-person interviews as part of the hiring process.

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; San Diego, CA, USA.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.

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.

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

Responsibilities

Learn more about benefits at Google .

• 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.

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 .