1. A computer-implemented method for layered training of machine-learning architectures, the method implemented by a training computing device including a processor coupled to a memory, the method comprising: receiving a plurality of data elements wherein each data element is associated with a timestamp; determining a training window for each model layer of a layered stack of model layers; determining a plurality of training data elements for each training window by identifying the data elements with timestamps corresponding to each of the training windows; identifying a previous checkpoint for each model layer, wherein the previous checkpoint for each model layer is generated by a parent model layer; training each model layer with the determined training data elements for each model layer and the identified previous checkpoint for each model layer; generating a plurality of current checkpoints, wherein each current checkpoint of the plurality of current checkpoints is associated with a model layer; storing the plurality of current checkpoints at the memory; and synchronizing an external server with at least one current checkpoint associated with at least one model layer, wherein the external server serves based at least partially on the synchronized current checkpoint.