generating an untrained model;

generating an intermediate representation of the untrained model, the intermediate representation in an intermediate language compatible with a virtual machine;

evaluating the performance of the untrained model, wherein evaluating the performance includes at least one of determining a latency in applying the untrained model in a target system, determining a frequency at which the untrained model can be applied in the target system, determining an amount of resources used by the untrained model, and determining an amount of power consumed by the target system using the untrained model;

iteratively generating and evaluating new untrained models, a new untrained model generated based on a performance of a previous model;

selecting a subset of models based on a performance of the generated new untrained models;

training the selected subset of models, thereby generating trained models;

evaluating an accuracy for each of the trained models; and

selecting a trained model based on the performance evaluation of the trained models for deployment to the target system.