Disclosed is a computer-implemented method for optimizing read thresholds of a memory device using a deep neural network engine, comprising reading, using a set of read threshold voltages applied to the memory device, data from the memory device under a first set of operating conditions that contribute to read errors in the memory device, producing a labeled training data set using the set of read threshold voltages under the first set of the operating conditions, determining, based on characteristics of the memory device, a number of layers, a size of each layer, and a number of input and output nodes of the deep neural network engine, training the deep neural network engine using the labeled training data set, and using the trained deep neural network engine to compute read thresholds voltage values under a second set of operating conditions.