Design and Implementation of AI-Enhanced Online Internship and Job Portal Systems

Authors

  • Chetana Sandip Patil Department of Computer Applications, GH Raisoni College of Engineering and Management, Jalgaon, India
  • Nehal Vijay Patil Department of Computer Applications, GH Raisoni College of Engineering and Management, Jalgaon, India
  • Divya Devidas Gavai Department of Computer Applications, GH Raisoni College of Engineering and Management, Jalgaon, India
  • Kalyani Raju Barwal Department of Computer Applications, GH Raisoni College of Engineering and Management, Jalgaon, India

Keywords:

Job Portal, Internship Management, Artificial Intelligence, Machine Learning, Recommendation Systems, E-Recruitment.

Abstract

The paradigm of recruitment has shifted significantly from traditional manual processes to sophisticated digital ecosystems. Online internship and job portals have become central to bridging the gap between talent and opportunities. This paper explores the architectural design, core functional modules, and technological stacks of modern job portals. Emphasis is placed on the integration of Artificial Intelligence (AI) and Machine Learning (ML) for resume parsing, intelligent recommendation engines, and candidate-job matching. By analyzing various implementations, including specialized systems for internships, blue-collar workers, and specially-abled individuals, this report provides a comprehensive overview of the current state and future directions of e-recruitment technology.

References

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Published

2026-09-29