Selected engineering work
RFID ML-serving platform
Verified active years: 2025
High-performance ML-serving APIs for real-time shelf mapping, built on Flask and Gunicorn and integrated with Azure Event Hubs and MongoDB. Engineered hot-reload capability so models update without downtime, plus monitoring, structured logging, automated scalability and fully containerised deployment.
My contribution
AI / ML systems engineer
Engineering contributions are described below.
Team / platform context
The description distinguishes system capabilities from personal contributions where the supplied evidence permits.
Engineering record
From implementation to production
The project description below records the supplied engineering work. A project-specific visualization has not been added.
Project description and engineering work
High-performance ML-serving APIs for real-time shelf mapping, built on Flask and Gunicorn and integrated with Azure Event Hubs and MongoDB. Engineered hot-reload capability so models update without downtime, plus monitoring, structured logging, automated scalability and fully containerised deployment.