We are looking for a hands-on Senior Computer Vision Architect to scale our live multi-camera video analytics platform from 100 to 1,000+ cameras across NVIDIA DeepStream and distributed edge device architectures. The ideal candidate must have strong production experience with NVIDIA DeepStream SDK, TensorRT optimization, edge AI deployments, and large-scale camera infrastructure. Responsibilities: • Design and manage a scalable 1,000-camera architecture with high availability and low latency • Optimize DeepStream pipelines (NvInfer, NvTracker, NVDEC, GStreamer) for stable FPS under heavy load • Deploy an manage CV models on Jetson or equivalent edge devices • Fine-tune YOLO models and export optimized TensorRT engines • Build and improve infrastructure using Doc...
I have a growing library of MP4 recordings of casino-grade slot machines and I need a reliable way to turn each session into structured data. For every spin I want the script to capture the start time, end time, bet size, win amount, any bonus triggers, and jackpots, then tally an overall spin count. The videos cover many different games, so the screen layout shifts from title to title; your solution therefore has to locate each region of interest on its own instead of relying on hard-coded coordinates. Because bonuses and jackpots are marked with visually distinct graphics, you can leverage that cue when classifying events. Accuracy matters more than raw speed, but I still expect processing to run unattended once configured. Please build a computer-vision / OCR pipeline that: • Au...
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