Company: ETIOT

Experience: 5 Years

Location: Kolkata | Work from Office

Department: Engineering / Product Development

Role Overview ETIOT is looking for a hands-on Video Analytics (VA) & Video Management System (VMS) Engineer with robust software development, video integration, and AI-powered computer vision experience. The candidate will work on integrating IP Cameras/CCTV systems, video streaming protocols, VMS platforms, and AI/ML-based analytics to build scalable, real-time video intelligence solutions across edge, cloud, and hybrid environments.

The role requires practical expertise in video processing, system integration, performance optimization, and deploying production-ready video surveillance and analytics applications.

Key Responsibilities

- Develop, integrate, and deploy Video Management Systems (VMS) and Video Analytics (VA) solutions supporting IP Cameras/CCTV, live video streaming, recording, playback, storage, and retention.
- Implement and troubleshoot ONVIF, RTSP/RTP, and related video streaming protocols, including interoperability across camera brands, codecs such as H.264/H.265, and third-party VMS platforms.
- Build real-time video processing and computer vision pipelines for object detection, object tracking, people and vehicle detection, ANPR/LPR, face detection/recognition, perimeter intrusion detection, loitering detection, PPE detection, crowd/behavior analytics, and video event detection.
- Develop and optimize AI/ML and Deep Learning models using OpenCV, PyTorch, TensorFlow, or similar frameworks.
- Work with C (strongly preferred) and Python for video processing, analytics integration, system development, and debugging.
- Leverage FFmpeg/GStreamer, NVIDIA CUDA, and TensorRT for video pipeline development, GPU acceleration, and inference optimization.
- Design and integrate REST APIs, WebSocket interfaces, microservices,



and API-first components for seamless communication between VMS, analytics engines, and external applications.
- Deploy and maintain solutions on Linux-based systems using Docker/Kubernetes, with data storage and messaging components involving PostgreSQL, MongoDB, Redis, or equivalent technologies.
- Contribute to VMS Architecture, Video Analytics Architecture, System Design, and Product Architecture for distributed, multi-camera deployments.
- Support edge AI, cloud/hybrid video processing, GPU-based processing, and distributed video processing architectures.
- Build scalable, highly available, real-time video solutions with multi-camera architecture and, where applicable, multi-tenant SaaS capabilities.
- Conduct integration testing, performance benchmarking, troubleshooting, and production deployment across different hardware and software environments.

Required Technical Skills
- Video &

• VMS:

Video Management System (VMS), Video Analytics (VA), IP Camera/CCTV integration, Video Streaming, Video Recording &

• Playback, Video Storage &

• Retention.

- Protocols &

• Codecs:

ONVIF, RTSP/RTP, H.264/H.265.
- AI/ML &

• Computer Vision:

Deep Learning, OpenCV, Object Detection, Object Tracking, ANPR/LPR, Face Detection/Recognition, People &

• Vehicle Detection, Perimeter Intrusion Detection, Crowd/Behavior Analytics, PPE Detection, Loitering Detection, and Video Event Detection.

- Programming &

• Video Processing:





C (strongly preferred), Python, FFmpeg/GStreamer.
- AI Acceleration &

• Frameworks:

NVIDIA CUDA, TensorRT, PyTorch, TensorFlow.
- Backend &

• Integration:

REST APIs, WebSocket, Microservices.
- Infrastructure &

• Data:

Linux, Docker/Kubernetes, PostgreSQL, MongoDB, Redis, or equivalent technologies.

Architecture & Engineering Competencies
- VMS Architecture and Video Analytics Architecture.
- Real-time Video Processing and Distributed Video Processing.
- Multi-camera architecture and scalable system design.
- High Availability and performance optimization.
- Edge AI, Cloud/Hybrid Architecture, and GPU-based Video Processing.
- Multi-tenant SaaS and API-first Architecture.
- System Design, Product Architecture, and end-to-end integration ownership.

Preferred Profile
- 5 years of relevant experience in video software engineering, VMS development, video analytics, computer vision, or video platform integration.
- Demonstrated hands-on experience integrating multiple IP camera models, VMS platforms, video streams, and AI analytics engines.
- Strong debugging and problem-solving skills across video protocols, networking, streaming, inference, and deployment environments.
- Experience taking solutions from proof of concept to production, including performance tuning and operational troubleshooting.
- Ability to collaborate across software, AI/ML, infrastructure, and product teams.

Ideal Candidate A software-oriented engineer who understands how cameras, video protocols, VMS platforms, AI/ML models, and distributed systems work together. The candidate should be capable of building and integrating end-to-end video intelligence solutions, with a strong emphasis on practical implementation, reliable deployment, and scalable product engineering.

📌 Video Analytics & VMS Engineer (Kolkata)
🏢 ETIOT INNOVATIONS
📍 Kolkata