The escalating pace of technological advancement worldwide precipitates an exponential demand for experts in the field of computer science. In this dynamic landscape, the requisite skills and proficiency in computer science have become paramount while human resource specialists and recruiters are confronted with an unprecedented amount of Curriculum Vitae (CV) daily, emphasizing the need for a technological solution such as a resume parser to streamline the evaluation process. This study is carried out with the aim of facilitating a more streamlined recruiting process using a text mining-assisted resume interpreter, particularly for Software Engineering positions. With the use of a dataset compiled from a combination of Software Developer vacancies, programming-centered resumes, and non-technical curriculum vitae, a linear Support Vector Machine (SVM) model is constructed and deployed on a web application. To evaluate the model's performance, metrics such as model accuracy, precision, recall, F1, and cross-validation scores were utilized.