Website:
opashsoftware.com
Job details:
The right candidate's profile will clearly say things like:
• "deployed YOLO with TensorRT for real-time video"
• "built multi-camera RTSP / GStreamer pipelines"
About the Role
We run real-time people- and vehicle-analytics on live CCTV cameras. The whole system runs on-premise on GPU machines (not in the cloud). Your job is to own the video pipeline end to end:
• Pull in many live camera streams (RTSP)
• Run object detection (YOLO) optimized to run fast
• Track people and vehicles across video frames
• Turn those tracks into useful analytics (counting, zones, queues, parking)
• Keep it all running reliably, with low delay, around the clock
You will rarely train a model from scratch. You will make detection and tracking fast, stable, and production-ready.
What You'll Do
• Build and maintain real-time video pipelines (RTSP camera input → live detection → tracking → analytics)
• Optimize models for speed using TensorRT (and/or ONNX) so they run in real time on our GPUs
• Implement and tune multi-object tracking (ByteTrack / DeepSORT)
• Debug live production issues: latency, dropped frames, GPU memory, multi-camera scaling
• Run and maintain the system on Linux GPU servers (on-premise/edge)
Required (Must Have)
• Strong Python for real production software (not just notebooks/scripts)
• Real-time video pipelines: RTSP camera ingestion, GStreamer or FFmpeg, frame handling, low-latency inference
• YOLO in production — deploying/optimizing models with TensorRT (running optimized engines, not just raw PyTorch files)
• Multi-object tracking: ByteTrack, DeepSORT, or similar
• Running computer vision on NVIDIA GPUs on-premise / edge (desktop GPUs or Jetson), on Linux
• Comfortable debugging live, always-on systems
Nice to Have
• OpenCV, PyTorch (for occasional fine-tuning / retraining)
• OCR / license-plate reading (ANPR) pipelines
• Re-identification (Re-ID), occupancy / zone-based analytics
• Messaging between services (e.g. ZMQ), integrating with a Node/web backend
Click on Apply to know more.