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AI Engineer with less than a year in GenAI, Machine Learning, and NLP, applied through diverse proje
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Highly motivated Data Science professional with a Bachelor of Technology in Mechanical Engineering, specializing in GenAI, Machine Learning, and Natural Language Processing. Proficient in Python, SQL, and various ML/DL frameworks, leveraging these skills to develop innovative solutions in areas like medical Q&A, e-commerce chatbots, and real estate research. Committed to creating impactful AI-driven applications and continuously expanding expertise in emerging technologies.
Jalpaiguri Govt. Engineering College
Bachelor of Technology · Mechanical Engineering
N/A – June 30, 2020
Medical Assistant
June 24, 2026 – Present
Developed a medical question-answering assistant by fine-tuning the LLaMA-3.2-1B model on 10,000 curated medical samples using LORA, integrated with a Retrieval-Augmented Generation (RAG) pipeline via ChromaDB to deliver evidence-backed medical insights. Built an interactive Streamlit application enabling PDF ingestion, context-based evidence retrieval, and accurate medical Q&A for enhanced user experience.
View ProjectE-Commerce Chatbot
June 24, 2026 – Present
Designed and implemented an AI-powered E-Commerce chatbot using RAG with LLAMA 3.3 integrated via GROQ API, ChromaDB and Sentence Transformers, enabling context-aware and natural language product search on a 5,000+ item dataset. Developed an end-to-end pipeline with SQLite-backed product data management, semantic intent classification, and a Streamlit-based interactive UI, achieving sub-second query responses and enhanced product discovery in testing scenarios.
View ProjectReal Estate Research Tool
June 24, 2026 – Present
Developed a user-friendly GenAI-powered research tool enabling users to input news article URLs and instantly retrieve accurate, source-backed insights from the real estate domain using Retrieval-Augmented Generation (RAG), advanced LLM prompting (Llama 3 via Groq), LangChain and ChromaDB. Engineered robust content processing workflows-automating article ingestion, embedding generation with HuggingFace, and sophisticated prompt-based LLM question answering (Llama 3 via Groq)-demonstrating versatility for real estate and adaptability across domains.
View ProjectVehicle Damange Detection App
June 24, 2026 – Present
Fine-tuned ResNet50 using transfer learning on ~1,700 images across 6 vehicle damage classes (Front/RearNormal, Crushed, Breakage), achieving ~80% validation accuracy.
View ProjectDeep Learning: Beginner to Advanced
Codebasics
June 1, 2025 – Present
Master Machine Learning for Data Science
Codebasics
May 1, 2025 – Present
Cultural Fit Analysis
The candidate's personal projects demonstrate strong initiative and self-directed learning, which are positive indicators for cultural fit in an innovative environment. The focus on practical application of AI technologies aligns well with roles requiring hands-on development. The breadth of projects, from NLP/GenAI to computer vision, shows a versatile interest in AI sub-fields. However, the lack of professional experience means there's no direct evidence of collaboration within a corporate structure or alignment with specific company values beyond technical aptitude.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive and hands-on approach to problem-solving, with a focus on developing functional applications. The diversity of projects (medical, e-commerce, real estate, computer vision) suggests adaptability and a willingness to explore different domains. The use of Streamlit for interactive UIs implies an understanding of user experience in AI applications. However, without direct work experience, it's difficult to assess collaboration, stress handling, or communication in a team setting.