Platform System Architect, Silicon
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Minimum qualifications:
- Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience.
- 3 years of experience with computer architecture concepts, including micro architecture, cache hierarchy, pipelining, and memory subsystems.
- 3 years of experience working with Mobile/Embedded SoCs architecture or use case system design.
Preferred qualifications:
- Master’s Degree in Computer Science, Electrical Engineering, or Computer Engineering, or equivalent practical experience.
- Experience working with Mobile/Embedded SoCs related to optimal system design to improve use case level power and performance.
- Experience with Android Architecture, Mobile SoC architecture, ML architecture, Computer Architecture, Performance, Power, Area (PPA) trade-offs.
- Knowledge of interactions between software and hardware IP blocks, general and special purpose compute units.
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
- Influence Tensor SoC architecture decisions for optimal Performance, Power, Area (PPA) working cross-functionally with Software/Hardware (SW/HW) architects, design teams, and research teams.
- Enable the industrial best user experience on Pixel phone devices empowered by the latest and the most advanced Generative AI technologies provided by Google Deepmind research.
- Leverage a data-driven approach through on-goal profiling, simulation, and modeling to drive consensus around architectural decisions across the entire silicon organization and solve testing system design problems under ambiguous and urgent requirements.
- Drive the architecture specifications, system design documentation, workload analysis, modeling, and projection to influence and define future SoC architecture.
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