System Performance Engineer
Qualcomm · San Diego, CA
About this role
Qualcomm is hiring a mid-level Systems Engineer in the operations function based in San Diego, CA. The posting calls out experience with Python, C, CUDA, Linux. Compensation is listed at $99,400–$149,200 per year.
- Role
- Systems Engineer
- Function
- operations
- Level
- mid
- Track
- Individual contributor
- Location
- San Diego, CA
- Posted
- May 15, 2026
More roles at Qualcomm
Job description
from Qualcomm careers##
Company:
Qualcomm Technologies, Inc.
## Job Area:
Engineering Group, Engineering Group > PPT Systems Engineering
General Summary:
As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm Systems Engineer, you will research, design, develop, simulate, and/or validate systems-level software, hardware, architecture, algorithms, and solutions that enable the development of cutting-edge technology. Qualcomm Systems Engineers collaborate across functional teams to meet and exceed system-level requirements and standards. Qualcomm's System Performance Team is responsible for optimizing and validating performance for Qualcomm Snapdragon Chipsets across all business units such as Mobile, Compute, Automotive, and IOT. In the role of System Performance Engineer, you will collaborate with software, hardware, and architecture teams to optimize power, performance, and thermal behavior of the system and be a technical lead to junior engineers across multiple projects. You will leverage your advanced systems knowledge and experience to research, simulate, and validate performance and ensure product requirements are met.
Key Responsibilities
· Enable, profile and analyze complex concurrent system use-cases in both emulation and software environments (Android/Linux/Windows)
· Define and document performance and power analysis plans for system use-cases across multiple workloads (CPU, GPU, AI/ML) as well as concurrent scenarios.