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Mid-level QA role in metro with common title and 2–5 year band increases applicant competition.
Role requires domain-specific video analytics, ONVIF/NVR and ML evaluation expertise, limiting cross-industry portability.
Explicit years plus mandatory AI/video, automation, and tooling skills make shortlisting highly strict.
Own quality assurance for AI-driven video analytics products including AI accuracy, functional, integration, and performance testing.
Develop and implement test strategies, automation scripts, and datasets to ensure reliable performance on real cameras and edge devices at scale.
Validate AI metrics such as precision, recall, and false-alarm rates, and conduct hardware testing including resource usage and stability on edge devices and GPU servers.
2-5 years of software QA experience with hands-on testing of video, CCTV/VMS, IoT, or AI/ML products.
B.Tech/BE/MCA in Computer Science, IT, Electronics or equivalent degree.
Proficient in Python scripting for test automation and API testing using tools like Postman, pytest, or requests.
Familiarity with Linux command line, Docker, IP cameras, RTSP/ONVIF protocols, video codecs, and NVR/VMS platforms.
Experienced in applying QA methodologies, defect lifecycle management, and Agile/Scrum practices specifically in video analytics or AI product environments.
Capable of building comprehensive test automation frameworks integrating video stream simulation and multi-camera systems.
Strong understanding of machine learning evaluation metrics such as precision, recall, mAP, and confusion matrix for AI accuracy validation.