As technology advances, processes that heavily utilize energy and require extensive cooling are constantly pushing the boundary of available computing solutions. Our team is utilizing machine learning models to simplify the design of cooling systems that would be used on supercomputers and data centers. The design cycle includes physical modelling of novel heat exchangers, assessing their performance via computational fluid dynamics simulations, training a machine learning algorithm, and 3D-printing an optimized heat exchanger.