Power Engineer (RTL Design) - RTL Engineer with Design Experience Job

Role: Power Engineer (RTL Design)
Location: Sunnyvale CA or Austin TX (Onsite)
Mode of Hiring: Full Time or Contract

RTL Engineer with Design Experience

• Please look for design engineers with power analysis experience
• Verification engineers with power aware verification or low power design verification experience.
• ASIC/SOC power engineers with experience on tools like PTPX / RTL-A.

We are seeking a highly skilled and motivated Contract Worker or Full Timer for RTL Design and Verification with expertise in power profiling and automation. The ideal candidate will play a crucial role in the analysis of power consumption, identifying hardware events that correlate with power consumption. Candidates will build run-time power models using Machine Learning techniques.
Key Responsibilities:
• RTL Design and Verification: Run power tests on RTL designs and verify that the test behavior matches the intent.
• Power Profiling: Utilize tools such as PPRTL or PTPX to perform comprehensive power profiling of hardware designs, identifying power-intensive areas and opportunities for optimization. Correlate various hardware events/telemetry with power profiles to understand power consumption.
• Data Processing and Automation: Develop and implement basic Python and/or TCL scripts for automation, data extraction, and processing of large volumes of hardware design data.
• Analysis and Reporting: Analyze profiling data, generate reports, and present findings to the design team, offering insights and recommendations for power reduction.
• Collaboration: Work closely with architects and designers to understand the power profile of the IP block and build a runtime power model using ML techniques.
Required Qualifications:
• Strong background in RTL design and verification principles.
• Demonstrable experience with power profiling tools such as PPRTL or PTPX.
• Proficiency in scripting languages like Python and/or TCL for automation and data manipulation.
• Ability to process and analyze large datasets related to hardware design.
Preferred Qualifications:
• Familiarity with machine learning models and their application in hardware design optimization is a plus.