AI Engineer (Computer Vision)
Summary
An AI engineer who deploys and integrates computer vision models onto edge devices, GPU systems and AI platforms (NVIDIA Jetson, TensorRT, ONNX), building real-time video processing apps that pull streams from IP cameras/NVRs and connect results to APIs, databases, dashboards and alarm systems. Core stack: Python, OpenCV, Linux.
Salary: $5,000 – $7,500 per month
AI Engineer (Computer Vision)
Build AI That Works in the Real World
We are looking for an AI Engineer (Computer Vision) to help bring AI and computer vision technologies from the lab into real-world applications.
You’ll work with cameras, video streams, AI models and edge computing platforms to build solutions that can see, analyse and respond to what is happening in the real world.
If you enjoy working across software, AI and hardware — and like solving problems where things don't always work perfectly the first time — this could be a great fit.
What You'll Be Doing
Deploy and integrate computer vision and AI models on edge devices, GPU systems and AI platforms.
Build and maintain real-time video processing applications.
Connect and work with video streams from IP cameras, NVRs and other camera systems.
Work with AI models using technologies such as PyTorch, ONNX and TensorRT.
Improve system performance, including speed, latency, GPU utilisation and multi-camera processing.
Deploy solutions on platforms such as NVIDIA Jetson, industrial PCs, GPU servers and AI Boxes.
Connect AI results to APIs, databases, dashboards and alarm systems.
Troubleshoot issues across video, software, hardware, networking and system performance.
Develop reusable tools and components for video streaming, AI inference, monitoring and system configuration.
Work closely with Computer Vision and R&D engineers to bring new AI models into working products.
What We're Looking For
Degree in Computer Science, Computer Engineering, AI or a related field.
Good programming skills in Python.
Hands-on experience with OpenCV and video processing.
Basic understanding of computer vision and AI/deep learning inference.
Experience deploying applications in a Linux environment.
Understanding of RTSP, video codecs, FPS, resolution and real-time video.
Good troubleshooting and problem-solving skills.
Some experience working with GPUs or hardware-accelerated AI.
It Would Be Great If You Also Have
Experience with any of the following:
ONNX Runtime | TensorRT | CUDA | FFmpeg | GStreamer | NVIDIA DeepStream | Docker | REST API | MQTT | NVIDIA Jetson | AI Accelerators | CCTV / IPC / NVR / VMS | Multi-camera Systems
Experience with model optimisation such as FP16, INT8 or quantisation is also a plus.