AI Engineer with less than a year in LLMs, RAG, NLP, and Machine Learning.
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Aspiring Generative Al Engineer with hands-on experience in LLMs, RAG, NLP, and Machine Learning through projects and internships. Proficient in Python, LangChain, ChromaDB for developing Al-powered applications. Eager to contribute strong problem-solving skills and build intelligent, scalable Al solutions.
Noida Institute of Engineering and Technology (NIET)
B.Tech · Computer Science & Engineering (Data Science)
August 1, 2022 – June 30, 2026
Ethara.ai
LLM Intern
April 1, 2026 – May 1, 2026
Gurgaon, Haryana, India
Primathon Technology
Associate Software Developer Intern
January 1, 2026 – March 1, 2026
Gurgaon, Haryana, India
Sales Forecasting Using XGBoost
June 1, 2026 – Present
Built an end-to-end ML pipeline using XGBoost to forecast Walmart sales, reduced RMSE by 18% compared to a baseline model. Performed data cleaning, preprocessing, EDA, and feature engineering using Pandas. Optimized model using hyperparameter tuning and evaluated using RMSE and MAE.
AI Video Assistant
June 1, 2026 – Present
Built an end-to-end Generative AI pipeline for audio/video processing using speech-to-text transcription and NLP. Developed LLM-based features using Mistral AI for summarization, title generation, and extraction of action items, decisions, and questions. Implemented a RAG-based Q&A system using vector embeddings and ChromaDB for contextual retrieval over transcripts and deployed via Streamlit for interactive querying.
Advanced RAG Chatbot
June 1, 2026 – Present
Developed a Retrieval-Augmented Generation (RAG) chatbot enabling natural language question answering over uploaded PDF documents. Built a semantic retrieval pipeline using LangChain, vector embeddings, and ChromaDB to provide context-aware responses from document content.
Programming Using Java
Infosys Springboard
June 1, 2026 – Present
Data Analysis with Python
Coursera
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects demonstrate a strong interest and initiative in AI/ML, particularly Generative AI, which aligns well with an AI Engineer role. The diversity of projects (video assistant, chatbot, sales forecasting) shows a breadth of application areas. However, the experience is primarily academic and personal projects, with limited professional experience, which might require more mentorship in a professional setting. The candidate is still pursuing a bachelor's degree, indicating a junior-to-mid-level fit for a senior role.
Soft Skills & Operational Fit
The candidate's resume highlights problem-solving, analytical thinking, team collaboration, and communication as soft skills. The psychometric test score of 308/500 suggests average performance in areas like logical reasoning, work attitude, stress handling, and team collaboration, indicating potential areas for development in operational fit. The English test score of 77/100 indicates good communication clarity.