Senior Computer Vision Engineer (Ref 26586)

Jobline Resources Pte Ltd; Singapore; On-site; SGD 150,000 - 210,000; Full time

Job summary

Jobline Resources Pte Ltd is seeking a software engineer to design and implement large-scale video analytics pipelines for multi-camera systems. You will work with Python and C++ to develop live analytics, telemetry, and enterprise integrations across VMS and NVR infrastructures.

You will optimize latency and throughput, leveraging NVIDIA DeepStream, GStreamer, Docker, and distributed messaging to deliver robust monitoring for smart city or enterprise deployments.

Qualifications

• 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).
• Elite proficiency in Python and performance-critical C++.
• Experience with PyTorch/TensorFlow, NVIDIA DeepStream SDK, GStreamer, Docker, and distributed message queues.

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).

Skills

Python

C++

Video analytics

Distributed systems

Real-time streaming

Tools

PyTorch

TensorFlow

NVIDIA DeepStream

GStreamer

Docker

Kafka

RabbitMQ

ONNX Runtime

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