#AI Infrastructure Software Engineer
Qualcomm
San Diego, CA1h agovia LinkedIn
AI Infrastructure Software Engineer
Qualcomm
About the Role
- Develop cutting-edge embedded software across the full system stack on Qualcomm Snapdragon® processors.
- Design, develop, and optimize core software frameworks for next-generation AI and compute workloads.
- Work on challenging low-level software problems involving inter-processor communication, memory management, execution environments, concurrency management, and DSP acceleration frameworks.
- Contribute to technologies enabling high-performance, power-efficient computing on industry-leading Snapdragon platforms.
Key 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.
Requirements & Tech Stack
- Strong programming skills in one or more languages such as C, C++, Java, or Python.
- Solid understanding of computer architecture, operating systems, and embedded systems concepts.
- Knowledge of real-time operating systems (RTOS) and concurrent software design.
- Experience with software debugging, performance analysis, and system optimization techniques.
- Familiarity with multimedia, compute, and driver frameworks on Linux, Android, or Windows platforms.
- Strong problem-solving skills.
Qualifications
- Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, Information Systems, or a related technical field.
Preferred Attributes
- Passion for learning new technologies, architectures, and operating systems.
- Experience developing software for multicore or heterogeneous processing environments.
- Interest in AI/ML acceleration, DSP technologies, and high-performance embedded computing.
- Self-starter with excellent collaboration and communication skills who thrives in a fast-paced engineering environment.