The success of an implant depends upon surface characteristics like roughness, topography, chemistry and hardness. The fabrication of a hard surface in combination with micron-, submicron- and nano-scale surface roughness is a great challenge for biomanufacturing industries. The surface microhardness (MH) needs to be maximized while controlling the Surface roughness (SR). The present research is the first study in which the application of Non-dominated sorting genetic algorithm (NSGA)-II coupled with Taguchi based Response surface methodology (RSM) is used to predict the optimal conditions of Powder mixed electric discharge machining (PMEDM) parameters to fabricate the biocompatible surface on β-phase Ti alloy. Batch vial tests were first carried out in accordance with the L₂₅ orthogonal array. ANOVA analysis gave the significant influencing factors and then mathematical models were developed between input parameters and output responses like SR and MH using Taguchi based RSM technique. These models were then optimized using NSGA-II to obtain a set of Pareto-optimal solutions. From the series of multiple solutions, the best optimal condition to achieve required low SR and high MH was determined, which are 13 A peak current, 5 μs pulse duration, 8% duty cycle (longer pulse-interval) and 8 g/l silicon powder concentration for achieving a required low SR and high MH. The MH considerably increased about 184% compared to the base material, and about 1.02 μm SR can be achieved in combination with micron-, submicron- and nano-scale surface features.