Abstract: A method and system for managing reproducible machine learning workflows are disclosed. The method includes receiving input comprising abstract data sets, and transforming abstract data sets into abstract data types. The method includes generating abstract pipelines using abstract data types, and implementing abstract pipelines as packages. The method includes configuring packages as map of key-value pairs comprising keys, and storing configured packages in database. The method includes generating execution plan by converting abstract pipelines from the configured packages into concrete pipelines. Further, method includes transmitting execution plan to orchestrator to merge individual concrete pipelines into dataset dependency graph, and to mark tasks in dataset dependency graph. The method includes executing tasks as cluster, by calling appropriate command, and obtaining predictions from different models or same model with different hyperparameters to provide meta construct, upon executing tasks as cluster.