Abstract: Methods and systems for generating entity embeddings for use with one or more machine learning models are described. The system comprises at least one storage device configured to implement a feature registry for storing features associated with at least one entity and at least one computer processor. The at least one computer processor is programmed to generate at least one entity embedding for the at least one entity, perform a plurality of benchmarking tasks on the generated at least one entity embedding to generate benchmarking data, and publish the at least one entity embedding and the benchmarking data to the feature registry to enable the at least one entity embedding to be shared among a plurality of machine learning models.