Staff Software Engineer - Video Analytics

Qualcomm • Santa Clara, CA

1d

About The Position

We are seeking a highly skilled Staff Software Engineer to design, implement, optimize, and deploy advanced computer vision and video analytics systems on resource-constrained edge computing platforms. This role has a strong emphasis on real-time surveillance, monitoring, and large-scale video intelligence applications. You will lead and contribute to research-driven development of computer vision algorithms, translating cutting-edge research into robust, production-grade systems. Working closely with cross-functional engineering and research teams, you will design, train, and deploy models for video understanding, object detection, tracking, and event recognition in real-world surveillance environments. You will also integrate modern computer vision frameworks and video streaming pipelines into embedded and edge software systems that power large-scale surveillance and media management solutions. In addition, you will document system architectures and research findings, troubleshoot and debug complex deployments, and continuously improve computer vision and media processing systems operating in the field.

Requirements

• Proven experience as a Software Engineer working on computer vision or video analytics systems, preferably in surveillance or monitoring contexts.
• Bachelor’s, Master’s, or Ph.D. degree in Computer Science, Computer Engineering, Electrical Engineering, or related research-intensive fields, with coursework or projects in computer vision or image processing.
• Strong programming experience in C++ and/or Python, with hands-on development of performance-critical computer vision pipelines.
• Solid understanding of multi-threading, asynchronous computing, coroutines, scheduling, and message-based systems used in real-time video processing.
• Proficiency with modern software engineering and debugging tools in Linux or embedded environments.
• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 4+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
• Master's degree in Computer Science, Engineering, Information Systems, or related field and 3+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
• PhD in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

Nice To Haves

• Demonstrated research experience in computer vision, including publications, patents, or applied R&D projects in areas such as object detection, tracking, video understanding, or scene analysis.
• Experience building surveillance, security, or intelligent video analytics systems, including camera pipelines, streaming, recording, and metadata extraction.
• Development experience with embedded systems and edge AI platforms optimized for real-time video processing.
• Strong problem-solving skills, self-motivation, and the ability to work independently while collaborating effectively with research and engineering teams.

Responsibilities

• Design, implement, optimize, and deploy advanced computer vision and video analytics systems on resource-constrained edge computing platforms.
• Lead and contribute to research-driven development of computer vision algorithms, translating cutting-edge research into robust, production-grade systems.
• Design, train, and deploy models for video understanding, object detection, tracking, and event recognition in real-world surveillance environments.
• Integrate modern computer vision frameworks and video streaming pipelines into embedded and edge software systems that power large-scale surveillance and media management solutions.
• Document system architectures and research findings.
• Troubleshoot and debug complex deployments.
• Continuously improve computer vision and media processing systems operating in the field.

Benefits

• competitive annual discretionary bonus program
• opportunity for annual RSU grants
• highly competitive benefits package

What This Job Offers

• Job Type: Full-time
• Career Level: Senior