System Performance Engineer

Minimum qualifications:

• Bachelor's degree in Electronics Engineering, Computer Engineering or Computer Science, or equivalent practical experience.
  
• 3 years of experience working with System Software of Silicon architecture, GPU and memory subsystem.
• Experience in power and performance optimization.
  
• Experience programming in Python, C, or C++.
  

Preferred qualifications:

• Master's degree in Electronics Engineering, Computer Engineering, Computer Science, or in a related techincal field.
• Experience in mobile System on a Chip (SoC) architecture and system software architecture.
• Experience in system hardware/software design for power, performance and thermal.
  
• Knowledge of Artificial Intelligence/Machine Learning (AI/ML) or Large Language Model (LLM) on the edge device.

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 Devices & Services team combines the best of Google AI, Software, and Hardware to create radically helpful experiences for users. We research, design, and develop new technologies and hardware to make our user's interaction with computing faster, seamless, and more powerful. Whether finding new ways to capture and sense the world around us, advancing form factors, or improving interaction methods, the Devices & Services team is making people's lives better through technology.

• Understand the Silicon Hardware and software architecture, design and implementation of a SoC.
• Understand software workloads and utilize the available compute engines on the Silicon.
• Define and validate key performance metrics (KPIs) and power goals for SoC and critical user journey workloads.
• Engage with ML System Architects and Software teams to define and validate Hardware/Software specifications.
• Engage with Verification and Validation teams to ensure KPIs are met.