This paper is about a feasibility study of applying a machine learning technique to derive aerosol properties from a single MAX-DOAS sky scan, which detects sky-scattered UV–visible photons at multiple elevation angles. Evaluation of retrieved aerosol properties shows good performance of the ML algorithm, suggesting several advantages of a ML-based inversion algorithm such as fast data inversion, simple implementation and the ability to extract information not available using other algorithms.