Freelance Senior Computer Vision Architect (DeepStream + Edge AI + Infra Scaling)
Budget: ₹750 – ₹1,250 INR
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 Docker, Kafka/MQTT, GPU clusters, load balancing, and autoscaling
• Improve real-time analytics dashboards and monitoring systems
• Document deployment workflows and architecture decisions
Required Skills:
• NVIDIA DeepStream SDK
• YOLO v5/v8/v9
• TensorRT, ONNX, TAO Toolkit
• Jetson Nano/Orin
• Docker, Kafka/MQTT, Nginx
• RTSP, ONVIF, H.264/H.265
• Python and C++
Experience Required: 5+ years in computer vision engineering
• 3+ years hands-on DeepStream experience
• Experience handling 250+ camera deployments
• Strong TensorRT optimization experience
To Apply:
Please include GitHub repositories, portfolio links, or case studies showing DeepStream pipelines or large-scale camera deployments.
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 Docker, Kafka/MQTT, GPU clusters, load balancing, and autoscaling
• Improve real-time analytics dashboards and monitoring systems
• Document deployment workflows and architecture decisions
Required Skills:
• NVIDIA DeepStream SDK
• YOLO v5/v8/v9
• TensorRT, ONNX, TAO Toolkit
• Jetson Nano/Orin
• Docker, Kafka/MQTT, Nginx
• RTSP, ONVIF, H.264/H.265
• Python and C++
Experience Required: 5+ years in computer vision engineering
• 3+ years hands-on DeepStream experience
• Experience handling 250+ camera deployments
• Strong TensorRT optimization experience
To Apply:
Please include GitHub repositories, portfolio links, or case studies showing DeepStream pipelines or large-scale camera deployments.
Related categories:
Python
Machine Learning (ML)
Artificial Intelligence
Docker
OpenCV
Computer Vision
Deep Learning
YOLO