DeepHyper is a software package that uses learning, optimization, and parallel computing to automate the design and development of machine learning (ML) models for scientific and engineering applications. DeepHyper reduces the barrier to entry for using AI/ML model development by reducing manually intensive trial-and-error efforts for developing predictive models. The package performs four key functions: pipeline optimization for ML (DeepHyper/POPT); neural architecture search (DeepHyper/NAS); hyperparameter search (DeepHyper/HPS); ensemble uncertainty quantification (DeepHyper/AutoDEUQ)