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AI Based Job Application Tracking System

Authors:

Kavitha Soppari, Assossiate Professor

Bharath Siddireddy, student

Dinne Police Shashank Reddy, Student

Dharavath Vigneshwar, Student

Department of CSE (AI & ML)

ACE Engineering College

Ankushapur, Ghatkesar Mandal, Telangana – 501301, India

ABSTRACT: This study presents an AI powered job application tracking system focused on promoting fair and unbiased candidate assessment. Built with ReactJS and Flask, the system leverages AI Ethics tools such as TensorFlow Fairness Indicators and IBM’s AIF360 to identify and reduce biases in hiring. Fairness metrics help detect potential biases in the application process, while reweighing techniques are applied to ensure that all the groups are represented equitably.

      In addition, the system performs soft skills analysis, using Hugging Face NLP models to examine candidates' activity descriptions for indicators of interpersonal skills. By integrating these fairness checks with soft skills insights, the system produces a balanced score for each candidate, helping organizations make more inclusive and transparent hiring decisions. This approach addresses bias in recruitment while offering a practical solution for fairer hiring practices.

Keywords: AI Ethics Tools, TensorFlow, AIF360 tool, Hugging Face Model, ReactJS, Flask.