Machine learning is becoming increasingly important and pervasive in people's lives, yet when its conclusions reflect biases that support ingrained prejudices in society, many vulnerable groups' psychological wellbeing may be impacted. To investigate if gender biases exist in image search engine algorithms that use machine learning, the study focuses on occupations. To do this, searches for various professions were run on Google, DuckDuckGo, and Yandex. Using web scraping techniques, a sample of images was retrieved for each selected profession and search engine. The images were then manually classified by gender, and statistical indicators and analyses were computed to detect potential biases in the representation of each gender. This analysis included a comparison between search engines, the calculation of mean, standard deviation, and coefficient of variation, a confidence interval an...