Design and Implementation of an AI-Powered Intelligent Job Portal using Machine Learning, WebRTC, and Real-Time AI Integration

At this time, the majority of job portals have been reduced to simply a web site where recruited post job description and where applicants post resumes. In practice, the process of hiring is much more complicated: it involves screening, testing, interviewing, and a significant amount of back and forth exchanges. The market however does not provide any good matching jobs and the recruiters have to put up with numerous irrelevant applications, and all this slows down to a crawl and makes the entire process to appear sloppy. These issues are addressed through the creation of an AI based job portal as part of our final year capstone. The concept was triggered by observing the disjointed nature of the hiring process. As a rule, a site will simply allow companies to post jobs and the candidate to upload CVs. The hard work, scanning resumes, and/or conducting entry-level tests, or arranging interviews are done in different platforms. That piece meal fashion creates longer deadline and creates chaos. And thus we were aiming to integrate all these processes in a single and unified artificial intelligence-driven system. Our portal is operated not by a simple job board but by machine-learning and basic NLP to process resumes to achieve better matching. It also has the inbuilt messaging and video interviews to enable the recruiters and the candidates to chat without the need to go out of the site. Having all communication and evaluation operations within a single platform allows recruiters to stop moving through dissimilar tools during hiring processes. Having everything under one roof makes workflow very simplified and everything in order.As part of the development of this project, we developed the UI using React.js, and the back-end was developed using Node.js and Express.js. MongoDB is the database which stores all the data of users and jobs. Python was introduced with the express purpose of the machinelearning and data processing components. The entire system was organized in a way that it can be modified or enlarged in the future. In this paper, the approach to design, the implementation process are more detailed and how such a system could be used in real life situations in recruitment is also evaluated.