Jorge Sintes is a software engineer and researcher with a passion for building innovative applications and exploring new technologies. With a background in computer science and a strong focus on machine learning and web development, Jorge has worked on a variety of projects ranging from automation tools to research papers on anomaly detection in time-series data.
His website is jorgesintes.dev.
Built a Python client and MCP server for PureGym by reverse-engineering the app’s internal API and turning it into a reusable automation layer. The resulting package powers both a Telegram bot and an MCP interface for class search, booking management, live center status, and opening hours from LLM clients and other agent tools.
A web tool for practicing musical scales and keys, designed for daily use in my own music practice. Built with TypeScript, with ear-training and visualization features for structured instrument practice.
Research project exploring ways of combining VAEs with RNNs to detect anomalies in real-world time-series data from vehicle telemetry, including the design and training of novel hybrid architectures.