Sr. Computer Vision Engineer

CLPS Global; Singapore; On-site; SGD 180,000 - 260,000; Full time

Job summary

CLPS Global seeks a Senior Computer Vision Engineer to design scalable video analytics pipelines for hundreds of live CCTV feeds. You will implement real-time telemetry, cross-system integration and multi-camera tracking across enterprise security platforms.

You will work with NVIDIA DeepStream, OpenCV and modern ML frameworks, optimizing latency and throughput while ensuring robust data pipelines for C2, VMS and smart city monitoring.

Qualifications

• >5+ years in software engineering.
• 3+ years in large-scale video analytics or real-time telemetry.
• >Experience integrating video analytics with C2, VMS, Smart City or security monitoring platforms.

Responsibilities

• Design and develop scalable Python/C++ video analytics pipelines for hundreds of live camera feeds.
• Build solutions using NVIDIA DeepStream, GStreamer, OpenCV, PyTorch/TensorFlow and related CV frameworks.
• Convert outputs such as bounding boxes, object IDs and tracking into JSON/Protobuf telemetry.
• Integrate real-time alerts with Kafka, MQTT, RabbitMQ, gRPC or similar brokers.
• Develop multi-camera tracking and Re-ID capabilities.
• Implement spatial-temporal tracking across cameras and locations.
• Develop middleware/plugins for VMS, NVRs and enterprise security system integration.
• Optimize inference pipelines with TensorRT and GPU acceleration.
• Profile and benchmark to maintain sub-second end-to-end latency.

Skills

Large-scale video analytics

Real-time telemetry

Python

C++

Edge video processing

Multi-camera tracking

Re-ID

NVIDIA DeepStream

OpenCV

PyTorch/TensorFlow

TensorRT

ONNX Runtime

Kafka

MQTT

gRPC

JSON/Protobuf telemetry

VMS integration

Latency optimization

Tools

GStreamer

OpenCV

NVIDIA DeepStream

PyTorch

TensorFlow

Kafka

MQTT

gRPC

ONNX Runtime

TensorRT

WebRTC

RTSP

Job description

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.