AI Engineer - Video Surveillance

Job description

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 Software Engineer, you will design, develop, create, modify, and validate embedded and cloud edge software, applications, and/or specialized utility programs that launch cutting-edge, world class products that meet and exceed customer needs. Qualcomm Software Engineers collaborate with systems, hardware, architecture, test engineers, and other teams to design system-level software solutions and obtain information on performance requirements and interfaces. Role Overview We are seeking an experienced Engineer to work on **Video Surveillance as a Service (VSaaS) platforms.** The role involves developing and integrating **AI-driven video analytics** use cases using existing models, performing **profiling and performance optimizations**, and **debugging complex system-level issues** across edge and cloud components. The engineer will work closely with platform, AI, and systems teams to deliver scalable, reliable, and high-performance VSaaS solutions. **Minimum Qualifications:** Bachelor's degree in Engineering, Information Systems, Computer Science, or related field. Key Responsibilities - Design, develop, and integrate AI-based video analytics use cases using existing ML/DL models - Work on VSaaS platform components spanning edge devices, cloud services, and APIs - Perform performance profiling, optimization, and resource tuning (CPU, GPU, memory, latency) - Debug and resolve system-level and application-level issues in production/lab environments - Optimize video pipelines, inference workflows, and data paths for reliability and performance - Collaborate with AI, platform, DevOps, and QA teams to ensure end-to-end solution quality - Analyze logs, metrics, and traces to identify bottlenecks and stability issues - Contribute to technical design discussions, code reviews, and engineering best practices - Document designs, optimizations, and troubleshooting guidelines **Qualifications Experience -** **Required:** - Bachelors or Masters degree in Computer Science, Electronics, or a related field - 1+ years of hands-on engineering experience in video analytics, VSaaS, or related domains - Strong experience in **C/C++ and/or Python** (Go experience is a plus) - Hands-on experience with **VSaaS or video analytics platforms** - Experience integrating and deploying **pre-trained AI/ML models** for real-world use cases - Solid understanding of **performance profiling and optimization techniques** - Strong debugging skills across application, OS, and system layers - Experience with **Linux-based systems** and containerized environments (Docker/Kubernetes) **Preferred:** - Experience with **video pipelines** (RTSP, GStreamer, FFmpeg, codecs) - Familiarity with **edge AI deployments** and hardware accelerators (GPU/NPU) - Exposure to **cloud-native architectures**, microservices, and observability tools - Understanding of **CI/CD pipelines** and production-grade deployments