Abstract: Techniques for synthetic training data generation for machine learning are described. A user provides a synthetic training data generator with first set of images and a corresponding set of class identifiers each indicating a type of object depicted in a corresponding image. Each image depicts an object with a substantially or completely monochromatic or transparent background. A user also provides or identifies a second set of images to be used as backgrounds. The synthetic training data generator generates a plurality of images by overlaying one or more of the objects depicted in the first set of images over ones of the second set of images, and further generates labels for each of the plurality of images. The plurality of images and labels are used to automatically train and deploy a machine learning (ML) model.