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AI Engineer with 1+ years in Data Pipelining & Machine Learning
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AI/ML Engineer and Python Developer with hands-on experience designing and deploying intelligent systems using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and cloud-based AI infrastructure. Proficient in building end-to-end machine learning pipelines from data preprocessing, feature engineering, and model training using scikit-learn, to deploying generative AI solutions with Azure OpenAI, LangChain, and vector databases such as ChromaDB. Experienced in developing interactive AI-powered applications using Streamlit, building REST APIs with FastAPI, and delivering data-driven insights through advanced analytics and visualization using Pandas, NumPy, Matplotlib, and Seaborn.
Udaya Nath Autonomous College
Bachelor of Computer Application (BCA)
August 1, 2023 – June 30, 2026
PERFORMALYTIC (INDIA) PRIVATE LIMITED
Data Engineer Intern
August 1, 2025 – Present
India
Talentele
Data Analyst Intern
August 1, 2024 – March 1, 2025
India
Loan Approval Prediction
June 24, 2026 – Present
• Analyzed applicant financial and demographic data to identify key factors influencing loan approval decisions. • Performed data preprocessing, feature engineering, and handled missing values for model readiness. • Built and evaluated classification models (Logistic Regression / Random Forest) to predict loan approval outcomes. • Achieved high prediction performance and provided insights to improve risk assessment strategies. Impact: Helped simulate automated loan eligibility screening and reduced manual evaluation effort.
Customer Segmentation
June 24, 2026 – Present
• Conducted exploratory data analysis on customer purchase and behaviour data. • Applied K-Means clustering to segment customers based on spending patterns and engagement levels. • Identified high-value and at-risk customer groups to support targeted marketing strategies. • Visualized segment insights through interactive dashboards. Impact: Enabled personalized marketing recommendations and improved customer targeting.
Retail Sales Forecasting and Dashboarding
June 24, 2026 – Present
• Forecasted sales for 100+ SKUs using time-series models and historical data. • Visualized seasonal trends, top-selling categories, and stock alerts in Power BI. Impact: Improved inventory turnover rate and reduced stockouts by 22%.
YouTube Transcript Q&A using RAG (Retrieval-Augmented Generation)
June 24, 2026 – Present
• Built an end-to-end RAG pipeline that extracts transcripts from YouTube videos, chunks and embeds the content using Azure OpenAI's embedding model, and stores vectors in ChromaDB for efficient semantic retrieval. • Integrated Azure OpenAI's GPT LLM to generate accurate, context-aware answers grounded in retrieved transcript chunks, reducing hallucinations through document-backed response generation. • Designed an interactive Streamlit UI allowing users to input any YouTube URL, ask natural language questions, and receive instant AI-generated answers sourced directly from the video's transcript. • Implemented LangChain to orchestrate the retrieval and generation workflow, managing prompt templates, memory, and the seamless interaction between ChromaDB and the Azure OpenAI endpoints. • Applied text chunking strategies (recursive character splitting) to optimize context window usage and improve retrieval precision from long-form video transcripts. Impact: Enabled users to query hours of video content in seconds, significantly cutting research and note-taking time and demonstrating practical GenAI application development on cloud-based LLM infrastructure.
SQL with Microsoft Server
Infosys Springboard
June 1, 2026 – Present
Data Visualization with Power BI
Great Learning
June 1, 2026 – Present
SQL with Relational Database
IBM Cognitive Class
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project portfolio shows a strong interest in AI/ML and data-driven solutions, aligning well with an AI Engineer role. The diversity of projects, from traditional ML (segmentation, forecasting, prediction) to modern GenAI (RAG), indicates adaptability and a continuous learning mindset. The internship experiences demonstrate a willingness to gain practical experience in different data-related domains.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on end-to-end solutions, from data preprocessing to deployment, suggesting good problem-solving and project management skills. The impact statements in projects highlight a results-oriented approach. Collaboration is mentioned in the Data Analyst Intern role, indicating teamwork capability.