Build the AI Box for ForecourtIQ – Car Dealership Smart Camera System.
We are looking for an experienced AI / Computer Vision Engineer with strong skills in edge-based machine learning, Python, and ideally ROS 2, to help build the next generation of our ForecourtIQ smart camera system used in car dealerships.
We already have the cameras (Reolink Argus PT Ultra) and hardware platform (Raspberry Pi) in place.
Your role is to build the AI box software that runs locally on-site (or over the air if possible, any suggestions would be appreciated), processing video feeds from Reolink or RTSP cameras to identify new customers and returning customers using facial recognition and clothing recognition, and integrate this with our dealership notification tool.
What You’ll Be Building:
A lightweight real-time computer vision pipeline.
Local inference using models such as YOLO, OpenCV, or custom embeddings
Customer identification logic (new vs returning)
Optional: ROS 2-based pipeline for scalability, reliability, and modularity
Optional: Dockerised deployment for easy updates
Skills We’re Looking For
✔ Strong Python or equivalent development experience
✔ Experience with computer vision (OpenCV, YOLO, TF Lite, ONNX Runtime, or similar)
✔ Experience deploying ML models on small devices (Raspberry Pi, Jetson, mini PCs)
✔ Understanding of real-time video ingestion and optimisation
✔ Familiar with edge computing & event-driven architectures
✔ Bonus: Experience with ROS 2 nodes, topics, and QoS profiles
✔ Bonus: Experience building cloud APIs for camera/AI products
Ideal For:
Freelancers
Contractors
AI/ML engineers
Robotics/ROS experts
Developers who’ve built vision systems before
Project Type:
Remote or hybrid.
Contract / one-off build, with potential for ongoing improvements.
Immediate start.
How to Apply:
Please send your proposal, examples of previous computer vision or edge-AI projects.