A user interface may be generated to receive inputs for constructing a data processing pipeline that includes an orchestrator node, a preparator node, and an executor node. The preparator node may generate a training dataset and a validation dataset for a machine learning model. The executor node may execute machine learning trials by applying, to the training dataset and the validation dataset, machine learning models having different sets of trial parameters. The orchestrator node may identify, based on a result of the machine learning trials, an optimal machine learning model for performing a task. The data processing pipeline may be adapted dynamically based on the input dataset and/or computational resource budget. The optimal machine learning model for performing the task may be generated by executing, based on the graph, the data processing pipeline the orchestrator node, the preparator node, and the executor node.