In recent years, predicting an individual's MBTI type using multiple data sources has become a major research subject. In this paper, we explore the use of machine learning algorithms for MBTI prediction based on text data. Recently, many firms have begun shortlisting individuals based on their personality, as this increases job efficiency because the person would be able to work on what he is good at rather than what he is compelled to do.The personality model used in this model is Myers-Briggs Personality Type Indicator. The Myers-Briggs Type Indicator (MBTI) is a popular personality evaluation tool which separates people into 16 personality types based on their preferences in four domains. Recent study has revealed that machine learning algorithms can be used to identify an individual's MBTI type based on writing samples.In this paper, we propose a methodology to predict an individual's MBTI type using machine learning algorithms such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Text Analysis. We also link an individual's MBTI type to job roles to aid in the recruitment process.