Oríon is a framework for asynchronous hyperparameter optimization (HPO) built around two main principles: 1) HPO should be effortless to execute in common machine learning workflows 2) New HPO algorithms should be readily available for practitioners. In this talk we will present Oríon and its core design principles, followed by an integration example with Dask demonstrating its simplicity of use.