ISSN No:2250-3676 ----- Crossref DOI Prefix: 10.64771 ----- Impact Factor: 9.625
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(Peer Reviewed, Referred & Indexed Journal)


    SMART HIRE

    Saleha Farha 1, Dongala Tejaswi 2, Are Thanmai 3, Poloju Varshitha 4

    Author

    ID: 2757

    DOI:

    Abstract :

    The Increasing Competition In The Job Market Has Made Interview Preparation And Resume Optimization More Challenging For Candidates. Many Applicants Fail During Applicant Tracking System (ATS) Screening Due To Poor Alignment Between Resumes And Job Descriptions. Furthermore, The Lack Of Structured And Personalized Preparation Resources Limits Candidates’ Ability To Perform Effectively In Interviews. To Address These Issues, This Paper Presents Smart Hire, An AI-powered Interview Preparation Platform That Integrates Resume Optimization, Personalized Learning, And AI-driven Mock Interviews Into A Unified System. The Platform Analyzes Resumes For ATS Compatibility And Provides Actionable Recommendations For Improvement. It Also Generates Role-specific Learning Resources, Including Coding Challenges And Aptitude Questions. Additionally, The System Conducts AI-based Mock Interviews And Provides Real-time Performance Evaluation With Detailed Feedback. The Proposed System Offers A Structured, Efficient, And Scalable Approach To Enhance Candidate Readiness And Improve Job Selection Outcomes

    Published:

    20-4-2026

    Issue:

    Vol. 26 No. 4 (2026)


    Page Nos:

    2696 - 2701


    Section:

    Articles

    License:

    This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

    How to Cite

    Saleha Farha 1, Dongala Tejaswi 2, Are Thanmai 3, Poloju Varshitha 4, SMART HIRE , 2026, International Journal of Engineering Sciences and Advanced Technology, 26(4), Page 2696 - 2701, ISSN No: 2250-3676.

    DOI: