Senior Computer Vision Engineer

Experience: 5+ Years

Key Responsibilities

• Design, develop, and optimize scalable video analytics pipelines to process multiple live camera feeds concurrently.

• Develop computer vision applications using Python, C++, OpenCV, NVIDIA DeepStream, and GStreamer.

• Implement AI/ML models for object detection, classification, tracking, and real-time video analytics.

• Develop real-time event detection and alerting mechanisms using structured JSON/Protobuf metadata.

• Integrate event streaming solutions using Kafka, MQTT, gRPC, or RabbitMQ.

• Develop multi-camera tracking and Re-Identification (Re-ID) solutions to track objects across multiple camera feeds.

• Build integrations and middleware for Video Management Systems (VMS), Network Video Recorders (NVR), and enterprise security platforms.

• Optimize AI inference performance using NVIDIA TensorRT and ONNX Runtime to achieve low-latency processing.

• Work with real-time video streaming protocols such as RTSP, WebRTC, SRT, and HLS.

• Integrate computer vision applications with IoT sensors, perimeter security systems, and access control devices.

• Troubleshoot, benchmark, and improve system performance, scalability, and reliability.

Required Skills

• 5+ years of software engineering experience, with at least 3 years of experience in computer vision, video analytics, or real-time telemetry pipeline development.

• Strong programming proficiency in Python and C++.

• Hands-on experience with OpenCV, PyTorch, and TensorFlow.

• Strong experience with NVIDIA DeepStream SDK and GStreamer.

• Knowledge of object detection, object tracking, and multi-camera Re-Identification (Re-ID) techniques.

• Experience with Docker and distributed messaging systems such as Kafka, RabbitMQ, or MQTT.

• Good understanding of real-time streaming protocols, including RTSP, WebRTC, SRT, and HLS.

• Experience with model optimization and inference acceleration using TensorRT or ONNX Runtime.

• Knowledge of VMS, NVR, C2 platforms, or enterprise security systems.

• Understanding of networking, secure communication protocols, and hardware integration.

• Exposure to IoT sensors, access control systems, OSDP, Wiegand, and PLCs will be an added advantage.