Additionally, the MTE is not limited to the selection of a model from a given set of molecular features, but also optimises the feature space selection itself. This allows our MTE to tackle the problem of workflow composition described by Barbudo et. al. in their 2023 review of autoML workflows. Since our MTE requires only the identify of the molecules and their associated target values, we are able to generates numerous molecular descriptor sets allowing the combination of molecular representation, model and model configuration to be optimised as a whole. This allows for nuances of potential interactions between certain feature types and the models evaluated to be considered, tempered by our median pruning strategy.