Miguel León

Miguel León is Lead AI Developer at Fluid, responsible for the machine-learning systems that personalise the cashier per player, route deposits to the right method, and surface the behavioural signals operators use to make decisions about retention and fraud.

Miguel holds a PhD from Mälardalen University (MDU) in Sweden, where he also served as a university lecturer in AI and as a program coordinator. That academic foundation sits behind a deeply practical engineering practice: ML in a regulated cashier has to be auditable, explainable to a compliance team, and robust enough to fail safely when the input distribution shifts. Miguel's job is to make sure Fluid's AI components clear that bar.

Inside Fluid he works on the personalisation models, the fraud and abuse signals that protect both operator and player, and the experimentation infrastructure that turns 'we think this helps' into 'we measured the lift'. He pairs closely with the product team because the most useful ML in this category is the kind that is invisible until it is missing.

He writes about applied AI and ML in iGaming, fraud detection in payment flows, behavioural analytics under regulatory constraint, and the ML-engineering practices that keep models trustworthy in production.