This research work focuses on a process to improve sensor performance by optimizing the shape of receiver coils fabricated on the printed circuit board of a contactless inductive position sensor, or CIPOS® developed by HELLA GmbH & Co. KGaA. Unlike other optimization methods suggested in the literature, the rotor and the sensor outlines are regarded as non-modifiable inputs. The driving force behind this is the practical need for sensor replacements where the sensor fits precisely into the allotted space without any alterations or modifications to the surrounding environment. The research begins with addressing the common factors that cause errors in an inductive position sensor. To numerically describe the receiver coils in the MATLAB development environment, the sinusoidal wave equation in combination with the Fourier series was used. SimCIPOS, an internal corporate simulation environment, was utilized to predict the sensor performance. Furthermore, this research work addressed the use of Genetic Algorithm (GA) for solving the optimization problem. Two sensor systems—one with and another without any misalignments—were simulated and optimized to determine their optimal radial dimensions for receiver coils. The algorithm comprised of an objective function which was used to calculate a fitness value. The most suitable radial dimensions were determined based on this fitness value. After optimization, both the systems exhibited a notable decrease in error metrics and a signal strength increase of approximately 59 times and 72 times, respectively. The “Hardware Position Sensors” department of HELLA can utilize these research results to further develop the CIPOS® sensor, and the findings of this project work can provide a basis for future studies in this area.