Video Analytics Backend Engineer — Edge to Ingest & Alerts

Private Advertiser; Singapore; On-site; SGD 70,000 - 110,000; Full time

Job summary

Private Advertiser seeks a software engineer to transform camera streams into typed events and sensor alerts. You will engineer edge pipelines using RTSP, GStreamer, and DeepStream, with model inference via ONNX Runtime or TensorRT.

You'll publish events over MQTT and manage a robust central ingest with PostgreSQL/TimescaleDB for real-time dashboards. The role emphasizes time-series processing, anomaly detection, and tight integration across edge and cloud components, requiring strong Python,

Qualifications

• 1-3 years of Python in production.
• Experience with video work in OpenCV, GStreamer or DeepStream.
• Model inference using ONNX Runtime, TensorRT or PyTorch.
• SQL skills beyond basics.
• Familiarity with Docker and Linux.
• Jetson deployment experience; MQTT, TimescaleDB/time-series tools.
• Exposure to time-series anomaly detection.

Responsibilities

• Build edge detection and tracking pipelines from RTSP sources using GStreamer/DeepStream.
• Perform inference with ONNX Runtime, TensorRT or PyTorch.
• Create event streams with metadata and clip pointers; publish over MQTT.
• Design central ingest with PostgreSQL/TimescaleDB for deduplication and dashboards.
• Incorporate time-series analysis and sensor data correlations for incidents.
• Implement WebRTC relay and secure audit/log records.
• Challenge specifications and iterate on requirements.

Skills

Python

OpenCV

GStreamer

DeepStream

ONNX Runtime

TensorRT

PyTorch

SQL

Docker

Linux

Jetson

MQTT

TimescaleDB

Time-series anomaly detection

Tools

PostgreSQL

Job description

Private Advertiser seeks a software engineer to transform camera streams into typed events and sensor alerts. You will engineer edge pipelines using RTSP, GStreamer, and DeepStream, with model inference via ONNX Runtime or TensorRT.

You'll publish events over MQTT and manage a robust central ingest with PostgreSQL/TimescaleDB for real-time dashboards. The role emphasizes time-series processing, anomaly detection, and tight integration across edge and cloud components, requiring strong Python,