Power & Thermal Systems Engineer – Windows on Snapdragon

Qualcomm; San Diego (CA); On-site; USD 111,000 - 167,000; Full time

Job summary

Qualcomm Technologies, Inc. in San Diego, CA is seeking a software engineer to own analysis and optimization of compute workloads under power and thermal constraints for Windows on Snapdragon.

You will work with System engineers, software and hardware teams to improve performance and energy efficiency across CPU/GPU/AI workloads. The role emphasizes development of power and thermal management algorithms, system-level software optimizations, and applying machine learning to optimize how compute

Qualifications

• Bachelor's degree in Engineering, Information Systems, Computer Science, or related field with 2+ years of software engineering experience.
• Master's degree in Engineering, Information Systems, Computer Science, or related field with 1+ year of software engineering experience.
• PhD in Engineering, Information Systems, Computer Science, or related field.
• 2+ years of academic or work experience with programming languages such as C, C++, Java, Python, etc.

Responsibilities

• Own and drive the analysis of complex system level use cases spanning across various SoC technologies and improve performance under power and thermal constraints.
• Develop algorithms and techniques to optimize power consumption and thermal performance across compute use cases.
• Perform system level software optimizations using hardware and software power/thermal management techniques.
• Apply advanced machine learning techniques to solve system level power and thermal problems.

Skills

C

C++

Java

Python

Education

Bachelor's degree in Engineering/CS/IS

Master's degree in Engineering/CS/IS

PhD in Engineering/CS/IS

Job description

Qualcomm Technologies, Inc. in San Diego, CA is seeking a software engineer to own analysis and optimization of compute workloads under power and thermal constraints for Windows on Snapdragon.

You will work with System engineers, software and hardware teams to improve performance and energy efficiency across CPU/GPU/AI workloads. The role emphasizes development of power and thermal management algorithms, system-level software optimizations, and applying machine learning to optimize how compute