This paper describes the application of evolutionary search to the problem of Flash memory wear-out. The current method for establishing memory operating parameters is a time consuming and expensive manual process of destructive testing. Understandably this process is normally undertaken only at design time. The results are sub optimum solutions which do not minimise ware-out over the lifetime of the device. We establish the viability of a hardware platform that utilises an EA (Evolutionary Algorithm) to discover optimal operating parameter settings automatically. Here we describe this hardware and reveal results demonstrating an average life extension of between 250% and 350% over the factory set conditions with a maximum life extension exhibited of 700% for cells within the same device. Furthermore since the process is automated it is possible to leverage the spread between process lots to further enhance device specifications, facilitating the near no cost life extension of a split-gate Flash memory device.