Computer Vision Engineer | Video Analytics

Computer Vision | Deep Learning | Video Analytics

Noida, Uttar Pradesh (On-site)

3–6 years

Computer Vision | Deep Learning | Video Analytics

Job Snapshot

location

Noida, Uttar Pradesh (On-site)

experience

3–6 years

function

Computer Vision | Deep Learning | Video Analytics

reporting_to

AI Product Manager / Head of Software VA

work_nature

AI / Technical / Production-focused

Where this role sits

Sparsh is building an AI-driven video analytics stack covering ANPR, face recognition, people and vehicle analytics, intrusion and perimeter detection.

This role sits within the Software & Video Analytics (VA) team and works closely with product, backend, deployment and QA teams.

You will own computer vision models end-to-end, from dataset curation and model training to real-time inference and production deployment across large multi-camera sites.

The role

This role is:

Computer VisionDeep LearningVideo AnalyticsAIProduction-focused

What you’ll work on

Computer Vision Models

Design, train and fine-tune detection, tracking, classification and recognition models for real-world surveillance use cases

Real-time Video Analytics

Build inference pipelines for live RTSP/ONVIF camera streams using GStreamer, FFmpeg, DeepStream or equivalent technologies

Model Optimisation

Optimise models for edge and GPU deployment using quantisation, pruning, ONNX, TensorRT and OpenVINO/NPU toolchains

Data & Model Lifecycle

Own annotation guidelines, dataset versioning, augmentation, hard-negative mining and periodic retraining from field data

Production Integration

Expose video analytics through APIs, event schemas and metadata standards for NVR/VMS, dashboards and third-party platforms

Who this role is for

• • 3–6 years of hands-on computer vision or deep learning experience, with at least 2 years in production video analytics or surveillance
• • B.Tech/M.Tech in Computer Science, Electronics or a related field
• • Strong Python and solid PyTorch or TensorFlow skills, with experience in OpenCV and NumPy
• • Comfortable with C++ for performance-critical modules
• • Experience with object detection, multi-object tracking, OCR/ANPR and/or face recognition pipelines
• • Hands-on experience with ONNX, TensorRT, DeepStream/GStreamer, Docker and Linux
• • Understanding of RTSP/ONVIF, H.264/H.265 video codecs and camera imaging fundamentals

What you’ll learn here

• How production-grade computer vision models are built and deployed on real camera streams
• How AI models are optimised for edge devices and GPU platforms
• How video analytics systems are benchmarked across lighting, weather, camera angles and Indian scene conditions
• How computer vision models integrate with NVR/VMS platforms and customer systems
• How AI products move from proof of concept to production across large multi-camera sites

Why join Sparsh

• ✓Work on India's first STQC-certified, Made-in-India surveillance platform deployed at national scale
• ✓Ship AI that runs in the real world on live camera streams and in the field
• ✓Gain full-stack exposure across hardware, firmware, software and AI under one roof

Ready to build AI that works in the real world?

Applications are reviewed through the Sparsh career application process