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@article{200748,
        author = {Ayush Kank and Jayesh Kande and Laxman Dewasi and Mr. Amit Kukreja},
        title = {AI POWERED CAREER ASSISTANT},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {1658-1665},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=200748},
        abstract = {Contemporary job market is becoming more competitive, which is causing a divide between the career preparation of candidates and the expectations of industry. Despite the widespread implementation of AI in assisting recruitment, in the forms of job recommendation and resume parsing, existing systems are limited in their functionalities, and do not offer holistic career guidance. This thesis proposes an AI-Powered Career Assistant, an online service that offers end-to-end, customized career support to job seekers through the use of modern NLP algorithms. This system combines NLP, ML, and Large language models (LLMs) to perform automatic resume analysis, job recommender, and interview preparation. The proposed solution will be deployed through a scalable client-server architecture, with secure backend processing and an attractive, intuitive user interface. Early tests have shown greater candidate readiness, improved interview performance and greater confidence. By uniting many AI functions into one comprehensive offering, this system offers a holistic approach to career development and highlights the potential of AI in improving recruitment efficiency and employability.},
        keywords = {Artificial Intelligence, Large Language Model, Machine Learning, NLP.},
        month = {May},
        }