Embedded AI Infrastructure Engineer (DSP/IPC)

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

Benefits offered by this job

RSU grants

Discretionary bonus program

Competitive benefits

Job summary

Qualcomm Technologies, Inc. is seeking a versatile software engineer to develop embedded software across the full stack for Snapdragon processors, focusing on IPC, memory management, and DSP acceleration for AI and compute workloads.

You will design, implement, and optimize frameworks, debug and profile performance, and collaborate with cross-functional teams to deliver high-performance, power-efficient solutions for diverse applications such as machine learning, computer vision, AR/VR, and

Qualifications

• 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.

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.

Skills

C

C++

Java

Python

Education

Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, Information Systems, or related field

Job description

Qualcomm Technologies, Inc. is seeking a versatile software engineer to develop embedded software across the full stack for Snapdragon processors, focusing on IPC, memory management, and DSP acceleration for AI and compute workloads.

You will design, implement, and optimize frameworks, debug and profile performance, and collaborate with cross-functional teams to deliver high-performance, power-efficient solutions for diverse applications such as machine learning, computer vision, AR/VR, and