Machine Learning Intern

At Wiremind, the Data team is responsible for developing, monitoring, and evolving all ML-powered forecasting and optimization algorithms used in our Revenue Management systems. The team consists of Machine Learning Engineers, who develop and monitor ML models, and Data Engineers, who ensure smooth integration of these models into our software. Our algorithms are divided in 2 parts: ML models to forecast unconstrained demand, capacity and overbooking (e.g. boosted trees, deep learning), trained on historical data in the form of time-series; Constrained optimizations problems solved using linear programming techniques. CARGOSTACK is an end-to-end SaaS solution for airlines to manage their cargo business. It combines a Cargo Management System (CMS) with optimization modules leveraging AI models to provide forecast to support users when taking decisions such as setting the right level of capacity for sale (in kg and m3), the right price, the right overbooking level, or the best pallet build-up (think of a 3D-Tetris optimizer). As a Machine Learning Intern, with support from more senior ML Engineers, you will leverage state-of-the-art AI/ML methods and ironclad validation processes to deliver robust, interpretable prediction systems.