We focus on engineered water systems but also cover other drinking-water-related settings such as source water and drinking water treatment processes. First, we introduce ML and common ML models. Then, we summarize recent progresses on the applications of ML in safe drinking water supply from the physical, chemical, microbiological, and temporal perspectives. Finally, we present the challenges and outlook for applying ML to ensure safe drinking waters supply. We focus on the applications of ML to access and control key factors and etiologies that affect drinking water quality and public health, such as water pipeline failures, DBPs, heavy metals, OPs, biofilms, and antimicrobial resistance genes (ARGs). This is the first review summarizing the applications of ML in assessing and controlling water quality in municipal engineered water systems, while the applications of ML in other drinking-water-related settings are also discussed.