Senior ASIC Power Architect for ML Accelerators

Google; Sunnyvale (CA); On-site; USD 163,000 - 236,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

Google is seeking an ASIC Design Engineer to shape AI/ML hardware acceleration by developing power-efficient TPU architectures and associated power models. You will verify complex digital designs and contribute to power optimization strategies within TPU projects and data-center accelerators.

The role involves collaborating with cross-functional teams to drive power efficiency from design through verification, impacting Google's cutting-edge AI hardware used globally.

Qualifications

• Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or related field or equivalent practical experience.
• 8+ years of experience in silicon design or architecture (logic design, power architecture, performance, or SoC design).
• Experience with power design, power modeling, power architecture, or power reduction methodologies/techniques.

Responsibilities

• Contribute to power modeling and drive convergence to power goals.
• Investigate, specify, and deploy architectural and microarchitectural power optimization techniques.
• Define best practices and methodologies to achieve low-power designs.
• Collaborate with cross-functional software and system teams to create novel power management architectures to meet power goals.

Skills

Power modeling

Power architecture

Power reduction techniques

Open-ended power/performance problem

Education

Bachelor's degree (EE/CE/CS or related)

Master's degree (EE/CE/CS)

PhD (EE/CE/CS)

Job description

Google is seeking an ASIC Design Engineer to shape AI/ML hardware acceleration by developing power-efficient TPU architectures and associated power models. You will verify complex digital designs and contribute to power optimization strategies within TPU projects and data-center accelerators.

The role involves collaborating with cross-functional teams to drive power efficiency from design through verification, impacting Google's cutting-edge AI hardware used globally.