Computer Vision & Live Streaming Expert Needed (WebRTC, FFMPEG, NVR/DVR, Django, React)

Project Overview We have an existing Computer Vision & Live Streaming Platform that integrates WebRTC, FFMPEG, NVR/DVR sources, Django, FastAPI, React, and more. However, we are facing several technical challenges that are preventing us from scaling and deploying across multiple use cases. We are seeking a highly experienced individual or team specializing in real-time video streaming, scalability, and fault tolerance to troubleshoot, optimize, and enhance the system for production readiness. Retry logic implemented but not functioning reliably Intermittent stream failures Need a strong auto-recovery fault-tolerant solution 2. Camera Scalability Current limit: ~8 camera streams per server Must scale far beyond this while optimizing CPU/GPU/memory usage The same setup behaves differently on different servers 3. Configurable Multi-Use Case UI Need a single UI framework that can be configured for multiple CV use cases, such as: -Attendance tracking -Construction site monitoring -Fire detection -Theft / pickpocket analytics -Number plate recognition (ANPR) -Rather than writing new code per use case, we need a config-driven or drag-and-drop solution for: 1-Dashboards 2-Alerting 3-Reporting 4-Layouts 4. Environment Consistency / Deployment Code behaves differently across servers Need standard deployment scripting or containerization Prefer Docker/Kubernetes CI/CD approach What We Expect ✔ Deep troubleshooting of reliability and retry logic ✔ Scalability optimization (more cameras per server) ✔ Environment standardization: Docker/K8s CI/CD ✔ Modular configurable UI design ✔ Documentation + Knowledge Transfer Ideal Candidate -Proven experience with WebRTC + FFMPEG + NVR/DVR -Past work scaling video streaming systems in production -Strong in Python (Django / FastAPI) + React Cloud DevOps (AWS, Azure, GCP) -Microservice architecture, Docker & Kubernetes Strong problem-solving skills & ability to deliver production-quality solutions Deliverables -Reliable live streaming with working retry logic -Scalable architecture supporting higher camera loads -Configurable UI framework for multiple use cases -Deployment documentation -Knowledge transfer session Screening Questions (Must Answer) 1-Describe your experience using WebRTC + FFMPEG for live streaming from NVR/DVR sources. 2-Have you scaled camera streaming beyond 8–10 streams per server? What approach did you use? 3-How do you ensure environment consistency across multiple deployment servers? 4-Share an example of a configurable UI/dashboard you built that supports multiple use cases without additional coding. 5-What techniques or tools do you use for real-time monitoring and fault tolerance in streaming systems? 6-How do you ensure security in live streaming and NVR/DVR integrations? How to Apply Please include: 1-Relevant project examples 2-High-level approach to solve our challenges 3-Estimated timeline & pricing model Apply tot his job