全职 Sr. Computer Vision Engineer 工作, 薪水, CLPS Global 公司招聘中 - Ricebowl

Role Overview

We are looking for a Senior Computer Vision Engineer with strong experience in video analytics, computer vision, real-time streaming and high-throughput telemetry pipelines.

The role focuses on designing, scaling and deploying computer vision pipelines that process large numbers of live CCTV feeds and deliver real-time intelligence to centralized Command & Control (C2), Video Management System (VMS) and operational monitoring platforms.

The engineer will work across computer vision, edge video processing, multi-camera tracking, event streaming, enterprise integration and performance optimization.

Key Responsibilities

• Design and develop scalable Python/C++ video analytics pipelines for concurrent processing of hundreds of live camera feeds.
• Build solutions using NVIDIA DeepStream, GStreamer, OpenCV, PyTorch/TensorFlow and related computer vision frameworks.
• Convert computer vision outputs such as bounding boxes, object IDs and tracking information into structured JSON/Protobuf telemetry.
• Integrate real-time alerts with Kafka, MQTT, RabbitMQ, gRPC or similar event/message brokers.
• Develop multi-camera tracking and person/vehicle re-identification (Re-ID) capabilities.
• Implement spatial-temporal tracking to map subjects across cameras and physical locations.
• Develop middleware/plugins for integration with Video Management Systems (VMS), NVRs, CCTV platforms and enterprise security systems.
• Integrate video analytics with Command & Control / Smart City / operational monitoring platforms.
• Optimize inference pipelines using TensorRT, ONNX Runtime and GPU acceleration.
• Profile and benchmark systems to maintain sub-second end-to-end latency for real-time command-center applications.
• Work with real-time video streaming technologies including RTSP, WebRTC, SRT and HLS.
• Integrate perimeter security technologies such as virtual tripwires, laser barriers and IoT occupancy sensors.
• Interface with physical security and hardware layers including dry-contact relays, Wiegand-to-IP converters, OSDP and PLCs.
• Troubleshoot performance, networking, streaming and integration issues across distributed video analytics environments.
• Contribute to system architecture, technical documentation, deployment and production support.

Required Skills & Experience

Experience

• 5+ years of overall software engineering experience.
• 3+ years of hands-on experience in large-scale video analytics, computer vision or real-time video telemetry.
• Experience integrating video analytics with C2, VMS, Smart City, security monitoring or operational command platforms.