CareerMitra : AI Career Path Recommender
  • Author(s): Bhagyshree Jaywant Pawar; Divya Navnath Shinde; Payal Suresh Rathod; Aditi Dhyaneshwar Palave; Prof. Sandhya Ranvir
  • Paper ID: 1715173
  • Page: 1078-1081
  • Published Date: 16-03-2026
  • Published In: Iconic Research And Engineering Journals
  • Publisher: IRE Journals
  • e-ISSN: 2456-8880
  • Volume/Issue: Volume 9 Issue 9 March-2026
Abstract

This paper presents CareerMitra, an intelligent AI-powered career guidance system designed to assist students and professionals in making informed career decisions. The system integrates mobile application technologies and artificial intelligence to analyze user data and generate personalized career recommendations. The frontend of the application is developed using Java and XML in Android Studio, while the backend processing is handled using Python. Firebase cloud database services ensure secure storage and management of user information. Ollama with the LLaVA 7B model is utilized to process user inputs such as education, skills, interests, experience, and behavioral responses to generate accurate and contextual career suggestions. This integrated approach improves accessibility, scalability, and reliability, making CareerMitra a practical solution for modern digital career guidance and educational technology platforms.

Keywords

Artificial Intelligence, Career Guidance System, Android Application, Java, Python, Firebase, Ollama AI, LLaVA 7B, Recommendation System, Educational Technology.

Citations

IRE Journals:
Bhagyshree Jaywant Pawar, Divya Navnath Shinde, Payal Suresh Rathod, Aditi Dhyaneshwar Palave, Prof. Sandhya Ranvir "CareerMitra : AI Career Path Recommender" Iconic Research And Engineering Journals Volume 9 Issue 9 2026 Page 1078-1081 https://doi.org/10.64388/IREV9I9-1715173

IEEE:
Bhagyshree Jaywant Pawar, Divya Navnath Shinde, Payal Suresh Rathod, Aditi Dhyaneshwar Palave, Prof. Sandhya Ranvir "CareerMitra : AI Career Path Recommender" Iconic Research And Engineering Journals, 9(9) https://doi.org/10.64388/IREV9I9-1715173