In the material extrusion based 3D printing-fused deposition modelling (FDM), each material may require its own unique set of processing parameters and these parameters can be difficult to optimise and control. This can lead to variability in the final product and can make it challenging to produce parts with consistent quality. Indeed, it is difficult to consider specific FDM parameters to obtain optimum mechanical properties mainly in case of high grade polymers (HGPs) e.g. PEEK, PEK, PPS etc. With the high thermal gradient and heat distribution during their printing, possibilities of residual stresses and deformations are unavoidable, which directly affects its quality and mechanical properties. In this article, an ensembled Surrogate Assisted Evolutionary Algorithm (SAEA) based method is used to optimise the process parameters (layer height, print speed, print direction and nozzle temperature) to enhance the mechanical properties, considered as print quality, of PEEK considering print time into account. The solution obtained through the SAEA approach is further compared with the solution computed through Gray Relational Analysis (GRA) Taguchi, which is used as the benchmark method, to establish the superiority of the proposed one. The comparison indicates the SAEA based solution has 28.86% of higher Ultimate stress value, 66.95% of lower percentage of elongation and 7.14% of lower print time in comparison to the benchmark result. It has also been found that print direction has a greater role in deciding the optimum value of mechanical properties for FDM 3d-printed PEEK material.