Senior AI Video Analytics Engineer (Python | FFmpeg | Kafka | NVIDIA Triton | Computer Vision)

Job Overview We are building an enterprise-grade AI Video Intelligence Platform (VMS) that processes hundreds of live CCTV camera streams in real time. We are looking for an experienced Senior Backend / AI Video Analytics Engineer with strong expertise in video streaming, distributed systems, computer vision, and scalable backend architecture. If you have hands-on experience building production-grade video analytics platforms, we would love to work with you. Responsibilities: *Video Streaming & Processing 1. Design and maintain scalable RTSP video ingestion pipelines using FFmpeg and GStreamer 2. Optimize video streams through FPS throttling, frame sampling, motion filtering, and bandwidth optimization 3. Publish video frames and metadata to Apache Kafka for downstream AI processing 4. Ensure high-performance, low-latency processing across hundreds of simultaneous camera streams AI Analytics Pipeline - Develop Kafka consumers for real-time AI inference - Integrate NVIDIA Triton Inference Server - Deploy and optimize ONNX deep learning models - Build face recognition pipelines using: *SCRFD *ArcFace *Qdrant Vector Database - Optimise inference performance for GPU environments Live Streaming & Video Storage 1. Implement HLS live streaming and video restreaming 2. Build continuous recording services using MinIO / Amazon S3-compatible storage 3. Develop: - Video retention policies - Event clip generation - Snapshot services - Video evidence retrieval Platform & Backend Services 1. Develop multi-tenant configuration management 2. Build WebSocket-based real-time alerting services 3. Implement: - Detection visualization - Event exploration - Face gallery management - Event history APIs Infrastructure & DevOps 1. Manage Docker-based deployments 2. Maintain and optimize: - Apache Kafka - PostgreSQL - MinIO - NVIDIA Triton 3. Monitor application performance, health, and scalability 4. Troubleshoot production issues across streaming, AI inference, and distributed services Required Skills - Python (Advanced) - FastAPI / Flask - FFmpeg - GStreamer - RTSP / RTP / HLS - Apache Kafka - Docker - PostgreSQL - Redis - MinIO / Amazon S3 - NVIDIA Triton Inference Server - ONNX Runtime - OpenCV - Computer Vision - Face Recognition (SCRFD, ArcFace) - Qdrant Vector Database - WebSockets - Linux - Git Nice to Have - CUDA optimization - TensorRT - DeepStream SDK - Kubernetes - YOLO models - ByteTrack / DeepSORT - Multi-camera AI systems - Video Management Systems (VMS) - Edge AI deployments Ideal Candidate - 5+ years of backend development experience - 3+ years working with AI video analytics or computer vision - Experience building large-scale distributed systems - Strong understanding of event-driven architectures - Comfortable processing hundreds of concurrent video streams - Able to write clean, production-ready, scalable code Project This is a long-term engagement to build an enterprise AI-powered Video Management System (VMS) for commercial and industrial customers. The right candidate will have the opportunity to become a core technical contributor as the platform scales. To Apply Please include: 1. Links to similar AI Video Analytics or VMS projects. 2. Experience with FFmpeg, GStreamer, Kafka, and NVIDIA Triton. 3. Your experience with face recognition pipelines (SCRFD, ArcFace, etc.). 4. Your preferred tech stack and architecture for processing 500+ RTSP camera streams. 5. Your GitHub or portfolio (if available).