Key skills
AI
About this role
Minimum qualifications:
- Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience.
- 8 years of experience with ASIC power management architecture.
- 8 years of experience with hardware or software power control flows and methodology.
Preferred qualifications:
- Master's degree or PhD in Electrical Engineering, Computer Engineering or Computer Science, with an emphasis on computer architecture.
- 6 years of experience with power components, power modeling, and power management techniques such as Dynamic Voltage Frequency Scaling (DVFS)/Adaptive Voltage Scaling (AVS), etc.
- Experience with processor core architectures (such as ARM, x86, RISC-V, etc.) and IPs commonly used in SoC designs.
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
- Develop and support various electronic design automation (EDA) tool infrastructure and flows.
- Collaborate with cross-functional teams to debug failures (e.g., boards, software, manufacturing, design, thermal issues, etc.) in lab and simulation.
- Work with internal cross-functional teams, including software engineering teams, external silicon partners, and intellectual property (IP) vendors to functionally validate and parametrically characterize the silicon and correlate that results meet predicted values.
- Influence Tensor Mobile SoC power architecture decisions for optimal Power Purchase Agreement (PPA) working cross-functionally with product, architects, software, and implementation teams.
- Lead proposed solutions through the entire development life-cycle, guiding their evolution from concept to a Hardware/Software optimized system solution deployed within the SoC and through production Software.