AI Engineer with less than a year in Machine Learning & Generative AI
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AI/Data Science enthusiast with hands-on experience in Python, Machine Learning, Deep Learning, Generative AI, and data analysis. Skilled in building AI-driven and data-centric solutions using modern frameworks and tools, with strong problem-solving, analytical, and model development abilities. Passionate about applying AI technologies to solve real-world challenges through scalable and efficient solutions.
Edure Learning Institute
Diploma · Data Science with AI
June 1, 2025 – March 1, 2026
University of Kerala
Bachelor of Computer Application · Computer Application
August 1, 2022 – May 1, 2025
BlackBox Learning
AI Engineer Intern
May 1, 2026 – Present
India
Vectorless RAG Q&A System
January 1, 2026 – June 1, 2026
Developed a document-based Q&A application that enables users to query PDF documents using Large Language Models without vector databases or embeddings. Implemented full-context retrieval by passing entire document text directly to the LLM, eliminating the need for FAISS or similarity search pipelines. Integrated Groq's LLAMA 3.1 model via LangChain for fast, accurate responses grounded strictly in uploaded document content. Built an interactive multi-document chat interface using Streamlit with session state management, real-time response timing, and chat history. Utilized Python, LangChain, LangChain-Groq, Streamlit, and PyPDF for end-to-end development.
View ProjectLinkedIn Job Scraping & AI-Based Job Recommendation System
September 1, 2025 – December 1, 2025
Developed an automated LinkedIn job scraping system to collect real-time job listings, company names, locations, skills, and job descriptions from LinkedIn. Implemented web scraping and browser automation techniques to efficiently extract and store large volumes of job-related data. Performed data cleaning, preprocessing, and CSV dataset generation for further analysis and AI-based processing. Designed the system to support scalable job data collection and future integration with AI-driven recommendation features. Utilized Python, Selenium, BeautifulSoup, Pandas, and automation techniques for project development.
View ProjectStock Market Prediction System
May 1, 2025 – August 1, 2025
Developed a stock market prediction system using Deep Learning and LSTM neural networks to forecast future stock price movements. Performed data preprocessing, feature scaling, and time-series analysis on historical stock market datasets. Trained and evaluated predictive models to analyze market trends and improve prediction accuracy. Created graphical visualizations and trend analysis reports for better understanding of stock performance. Utilized Python, TensorFlow, Keras, Pandas, NumPy, and Matplotlib for model development and analysis.
View ProjectAI-Based Job Recommendation System
January 1, 2025 – April 1, 2025
Developed an AI-powered job recommendation system to match users with suitable career opportunities based on skills, interests, and personality traits. Integrated a 16-personality assessment model to analyze user behavior and improve recommendation accuracy. Applied Machine Learning algorithms and data analysis techniques for intelligent job role prediction and recommendation. Designed an interactive interface for personality assessment, job filtering, and recommendation visualization. Utilized Python, Pandas, Scikit-learn, Streamlit, and data visualization libraries for project development.
View ProjectDiploma in Multilingual Computer Application
DCA
June 1, 2026 – Present
Introduction to Generative AI and Agents
Microsoft Learn
June 1, 2026 – Present
GenAI Workshop
BlackBox Learning
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects demonstrate a strong interest and initiative in AI/Data Science, aligning well with a culture that values innovation and continuous learning. The diversity of projects (RAG, Recommendation Systems, Stock Prediction, Web Scraping) shows a broad curiosity and willingness to explore different AI applications. However, the candidate's experience level (currently an intern) suggests a need for mentorship and integration into a professional team environment. The cultural fit would depend on the team's capacity to support a developing AI engineer.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a problem-solving mindset and an ability to translate theoretical AI concepts into practical applications. The use of Streamlit for interactive interfaces suggests an understanding of user experience in AI tools. However, with limited professional experience (internship starting in May 2026), the depth of operational fit and collaboration skills cannot be fully assessed from the provided data.