Abstarct: One of the devices used in industry, which besides creating a vacuum also performs the task of mixing fluids with powdered and granular solids, is an ejector. Ejectors have various applications in industry, such as in refrigeration cycles as a replacement for compressors, for removing air and non-condensable gases in steam power cycles, and as a substitute for mechanical pumps to feed boilers with liquid water and create a vacuum in vacuum distillation columns. Ejectors are available in different sizes depending on process conditions, and due to the absence of moving parts, they have lower maintenance and operational costs than other vacuum-generating devices. They do not require repairs unless corrosion occurs, and even in the case of corrosion, their repair costs are significantly lower than those of vacuum pumps. One disadvantage of ejectors is their low efficiency, which is sensitive to the ejector's geometry. In this research, the geometry of the ejector was optimized using Fluent software and computational fluid dynamics (CFD) methods. The geometric parameters that have the most sensitivity to ejector performance were identified by reviewing scientific sources and available research. The geometry was parameterized in the software, and optimization was performed using a genetic algorithm with the help of ANSYS software. The problem was solved by considering 10 different geometric parameters as optimization variables and using two objective functions: the pressure ratio and the secondary fluid mass flow rate. The optimal values for these parameters were determined. This optimization resulted in a geometry that increased the ejector's efficiency from about 29% to approximately 42%. In fact, through this optimization, the two key parameters influencing ejector efficiency (pressure ratio and suction ratio) were maximized.