CPU Power Modeling & Energy Analytics Engineer

Google LLC; Austin (TX); On-site; USD 138,000 - 197,000; Full time

Job summary

Google LLC in Austin, TX, seeks an experienced CPU Architect to push the frontier of custom silicon for Google's direct-to-consumer products. You will own energy modeling, power analysis, and system-level optimization to deliver high-performance, power-efficient CPUs.

The role emphasizes collaboration across SoC teams and benchmarking across workloads. The team combines AI, software, and hardware to create fast, seamless computing experiences.

Qualifications

• Bachelor's degree or equivalent practical experience in Electrical/Computer Engineering or related field.
• 4 years of industry experience (Hardware) or equivalent research.
• Experience with low-power systems, power estimation, data analytics and profiling.
• Experience in flow automation (Python, C, C++, Gemini).
• Experience with data science.

Responsibilities

• Recruit a talented individual contributor engineer to own and drive CPU architecture and system-level energy modeling, performance and power analysis, optimization, simulation and rollups.
• Develop a system-level power model for battery life analysis and energy optimization.
• Collaborate with SoC and CPU Power Teams on power projections and requirements, including silicon power capture and profiling for benchmarks and workloads.
• Perform workload analysis for battery life and tests definition for power analysis and optimization.
• Perform data mining analysis at RTL and gate-level to define micro-architectural transactions for high-level power estimation.

Skills

CPU architecture

Power modeling

Energy analysis

Python

C

C++

Education

Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or related field

Tools

Gemini

Ansys Power Artist

Synopsys Prime Power RTL

PTPX

Job description

Google LLC in Austin, TX, seeks an experienced CPU Architect to push the frontier of custom silicon for Google's direct-to-consumer products. You will own energy modeling, power analysis, and system-level optimization to deliver high-performance, power-efficient CPUs.

The role emphasizes collaboration across SoC teams and benchmarking across workloads. The team combines AI, software, and hardware to create fast, seamless computing experiences.