Abstract: Presented herein are techniques for managing a plurality of machine learning engines. A method includes receiving at an orchestration entity information descriptive of attributes of a plurality of machine learning engines, generating, based on the information, a unique signature for each machine learning engine of the plurality of machine learning engines, creating, based on the unique signature for each machine learning engine, an ensemble of machine learning engines configured to operate on a predetermined task, causing the ensemble of machine learning engines to operate on the predetermined task, and monitoring performance metrics of the machine learning engines in the ensemble of machine learning engines while the ensemble operates on the predetermined task.