We present a case study of the performance testing of a commercially engineered genetic programming algorithm applied to the automated modeling of industrial machine learning problems. is paper summarizes some of what has been learned over the past ve years of working with a large number of industrial machine learning challenges in a commercial or enterprise se ing. Automation and parallelism via cloud computing is used to reduce test time.