Senior Computer Vision Engineer

Jobline Resources Pte Ltd; Singapore; On-site; SGD 120,000 - 170,000; Full time

Job summary

Jobline Resources Pte Ltd is seeking an experienced software engineer to architect and optimize large-scale video analytics pipelines for live camera feeds. You will implement cross-camera tracking, configure real-time streaming, and build integration points with VMS and access control systems.

The role emphasizes performance tuning, embedding models with NVIDIA DeepStream, and delivering sub-second latency from sensor to dashboard across enterprise environments in Singapore.

Qualifications

• 5+ years of software engineering experience, with 3+ years in large-scale video analytics pipelines.
• Proficiency in Python and performance-critical C++.
• Deep expertise in PyTorch/TensorFlow, DeepStream, GStreamer, Docker, and distributed queues (Kafka).
• Strong grasp of real-time streaming protocols (RTSP, WebRTC, SRT, HLS) and secure transport configurations.

Responsibilities

• Architect C2-scale analytics pipelines using Python/C++ across hundreds of live camera feeds.
• Translate model outputs into lightweight structured metadata payloads (JSON/Protobuf).
• Stream alerts to C2 brokers via Kafka, MQTT, or gRPC.
• Develop multi-camera tracking and fusion algorithms for cross-camera re-identification.
• Integrate with VMS, NVRs, and access control layers via plugins and middleware.
• Profile and optimize inference pipelines using TensorRT/ONNX Runtime to meet latency targets.

Skills

Python

C++

Video analytics

Distributed queues

Realtime streaming

Tools

NVIDIA DeepStream SDK

GStreamer

PyTorch

TensorFlow

OpenCV

Docker

Kafka

Job description

Responsibilities

• C2-Scale Analytics Pipelines: Architect robust Python/C++ pipelines using frameworks like NVIDIA DeepStream, GStreamer, or OpenCV to execute concurrent video analytics across hundreds of live camera feeds.
• Event Telemetry & Alert Generation: Translate computer vision model outputs (bounding boxes, track IDs) into lightweight, structured JSON/Protobuf metadata payloads.
• Stream these alerts instantly to C2 event brokers using Kafka, MQTT, or gRPC. Multi-Camera Tracking & Fusion: Develop algorithms for cross-camera re-identification (Re-ID) and spatial-temporal tracking, allowing the C2 system to map a subject's trajectory across a physical site or facility layout.
• VMS & Enterprise Integration: Write custom plugins and middleware to interface directly with enterprise-grade Video Management Systems, network video recorders (NVRs), and unified access control physical layers.
• Performance Tuning for Command Centers: Profile, benchmark, and scale inference architectures using tools like TensorRT or ONNX Runtime to maintain strict sub-second end-to-end latency boundaries from camera sensor to C2 dashboard.
• Perimeter Security Sensors: Virtual/physical tripwire sensors, laser barriers, and IoT occupancy sensors.
• Hardware Integration Layers: Dry contact relays, Wiegand-to-IP converters, OSDP (Open Supervised Device Protocol), and Programmable Logic Controllers (PLCs).

Requirements

• Experience: 5+ years of software engineering experience, with 3+ years specialized in deploying large-scale video analytics or telemetry pipelines integrated with operational monitoring systems (C2, VMS, or Smart City platforms).
• Programming Languages: Elite proficiency in Python and performance-critical C++.
• Frameworks & Infrastructure: Deep expertise in PyTorch/TensorFlow, NVIDIA DeepStream SDK, GStreamer, Docker, and distributed message queues (Kafka/RabbitMQ).
• Networking & Protocols: Thorough understanding of real-time streaming protocols (RTSP, WebRTC, SRT, HLS) and enterprise security transport configurations.

Licence no: 12C6060