Path to Placement – Connected Path from Resume to Job with Resume Optimizer and Job Recommendation

Authors

  • Dr. Shabina Modi Department of Computer Science and Engineering KBP College of Engineering (KBPCOE) Author
  • Pratik Satpute Department of Computer Science and Engineering KBP College of Engineering (KBPCOE) Author
  • Jay Shinde Department of Computer Science and Engineering KBP College of Engineering (KBPCOE) Author
  • Onkar Shinde Department of Computer Science and Engineering KBP College of Engineering (KBPCOE) Author

DOI:

https://doi.org/10.47392/IRJAEH.2026.0530

Keywords:

Artificial Intelligence (AI), Machine Learning (ML), Resume Optimizer, Job Recommendation System, Natural Language Processing (NLP), Employment Automation, Skill Matching, Career Guidance, Placement System, Data-Driven Recruitment

Abstract

In current times, the competitive nature of job markets poses problems for many students and job seekers regarding the effective bridging between skill demonstration and employment options. To solve this problem, there will be developed the Path to Placement System which will provide a comprehensive platform that helps the users get from resume preparation to employment seamlessly. In this proposed Path to Placement System, we will be incorporating two main components which are a Resume Optimizer and a Job Recommendation Engine, both of which are enabled by the Artificial Intelligence and Machine Learning technologies. The Resume Optimizer will use Natural Language Processing to analyze the resume prepared by the user in terms of structure, use of keywords, and relevancy of the skills provided. At the same time, the Job Recommendation Engine will utilize job APIs and data analytics to recommend the best jobs to the user considering the skills and experience.

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Published

2026-06-09

How to Cite

Path to Placement – Connected Path from Resume to Job with Resume Optimizer and Job Recommendation. (2026). International Research Journal on Advanced Engineering Hub (IRJAEH), 4(06), 4110-4114. https://doi.org/10.47392/IRJAEH.2026.0530