QA Engineer | Video Analytics

Software QA | AI Testing | Video Analytics

Noida, Uttar Pradesh (On-site)

2–5 years

Software QA | AI Testing | Video Analytics

Job Snapshot

location

Noida, Uttar Pradesh (On-site)

experience

2–5 years

function

Software QA | AI Testing | Video Analytics

reporting_to

AI Product Manager / Head of Software VA

work_nature

Quality-focused / Automation / AI Testing

Where this role sits

Sparsh's Software & Video Analytics (VA) team builds AI-driven analytics for ANPR, face recognition, people and vehicle analytics, intrusion and perimeter detection.

This role sits within the VA team and owns quality across AI accuracy, functional testing, integration, performance and field validation.

You will build test strategies, automation and datasets that ensure every release performs reliably on real cameras, in real conditions and at scale.

The role

This role is:

Software QAAI TestingTest AutomationVideo AnalyticsQuality-focused

What you’ll work on

Video Analytics Testing

Define and execute functional, regression, integration, performance, stress and security testing for video analytics modules

AI Accuracy Validation

Build ground-truth datasets and measure precision, recall, false-alarm rate, ANPR read rate, face recognition match rate and latency

Test Automation

Build repeatable automation using Python, pytest, Postman, REST APIs and video-replay or stream-simulation setups

Hardware & Performance Testing

Validate FPS, resource usage, thermal behaviour, memory leaks and long-run stability on edge devices and GPU servers

Integration & Field Testing

Test NVR/VMS, ONVIF cameras, alert channels and third-party integrations while converting field issues into regression cases and datasets

Who this role is for

• • 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
• • Strong understanding of QA methodology, test-case design, defect lifecycle and Agile/Scrum practices
• • Python scripting experience for test automation
• • Experience with API testing using Postman, pytest or requests
• • Familiarity with Linux command line, Docker, IP cameras, RTSP/ONVIF, video codecs and NVR/VMS platforms
• • Understanding of ML evaluation metrics including precision, recall, mAP and confusion matrix

What you’ll learn here

• How AI accuracy is validated using real-world video datasets and ground-truth data
• How video analytics products are tested across day/night, weather, camera angles and Indian scene conditions
• How automated testing is built for multi-camera video analytics systems
• How AI products are tested across edge devices, GPU servers, APIs, cameras and NVR/VMS platforms
• How field issues are converted into regression tests, datasets and product quality improvements

Why join Sparsh

• ✓Work on India's first STQC-certified, Made-in-India surveillance platform deployed at national scale
• ✓Test AI that runs in the real world on live camera streams and in the field
• ✓Gain exposure to AI, computer vision, software, hardware and video analytics under one roof

Ready to make AI reliable in the real world?

Applications are reviewed through the Sparsh career application process