Embedded AI Infrastructure Engineer

QUALCOMM, Inc.; San Diego (CA); On-site; USD 94,000 - 141,000; Full time

Job summary

Qualcomm Technologies, Inc. in San Diego, California, is seeking an AI Infrastructure Software Engineer to design, develop, and optimize embedded software across the full stack for Snapdragon processors.

You will tackle IPC, memory management, and DSP acceleration frameworks to enable high-performance AI and multimedia workloads. The role involves debugging and profiling across Linux/Android/Windows environments, with opportunities to contribute to future AI compute technologies.

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or related field.
• Proficiency in C, C++, Java, or Python.
• Strong understanding of computer architecture, OS, and embedded systems.
• Experience with RTOS, debugging, performance analysis, and system optimization.
• Familiarity with Linux/Android/Windows driver frameworks.

Responsibilities

• Design and implement embedded system software across multiple layers of the software stack.
• Develop and optimize inter-processor communication (IPC) and memory management solutions.
• Build software frameworks that enable efficient DSP acceleration for AI and multimedia workloads.
• Debug, profile, and optimize system performance across diverse hardware and software environments.
• Collaborate with cross-functional teams to deliver scalable, high-performance solutions for Snapdragon-based products.

Skills

C/C++

Java

Python

RTOS

Embedded systems

Debugging

System optimization

Linux/Android/Windows

Education

Bachelor's degree in CS/CE/EE or related field

Job description

Qualcomm Technologies, Inc. in San Diego, California, is seeking an AI Infrastructure Software Engineer to design, develop, and optimize embedded software across the full stack for Snapdragon processors.

You will tackle IPC, memory management, and DSP acceleration frameworks to enable high-performance AI and multimedia workloads. The role involves debugging and profiling across Linux/Android/Windows environments, with opportunities to contribute to future AI compute technologies.