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AI Engineer with less than a year in Machine Learning & NLP
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M.Sc. AI graduate with two ML internships (Infosys Springboard & Virtusa) and 6 deployed projects. Built a loan default risk system achieving 94.59% accuracy on 148,670 records using LightGBM. Skilled in Python, NLP, RAG pipelines, LLM integration, SQL, FastAPI and Streamlit. Seeking AI/ML, Data Science, or SQL roles. Open to relocation.
Bharathidasan University
M.Sc. Artificial Intelligence · Artificial Intelligence
August 1, 2023 – June 30, 2025
St. Joseph's College
B.Sc. Computer Science · Computer Science
August 1, 2020 – June 30, 2023
Infosys Springboard
Machine Learning Intern
February 1, 2026 – April 30, 2026
India
Virtusa
Machine Learning Intern
February 1, 2025 – May 31, 2025
Chennai, Tamil Nadu, India
GenZ Bank System
April 1, 2026 – April 30, 2026
Built banking database system simulating account creation, deposits, withdrawals and transactions. Implemented SQL procedures and constraints to ensure data integrity and support core banking operations.
View ProjectGroundCheck – RAG-Powered YouTube Q&A System
March 1, 2026 – March 31, 2026
Built end-to-end RAG pipeline fetching YouTube transcripts, creating vector embeddings via sentence-transformers stored in ChromaDB. Generated grounded answers using Llama 3.3 70B via Groq API with hallucination detection and strict prompt engineering.
View ProjectCreditPath AI – Loan Default Risk Assessment
February 1, 2026 – April 30, 2026
LightGBM model - 94.59% accuracy, ROC-AUC 0.986 on 148,670 records with expected loss computation and 4-tier risk classification. Role-based web app (Applicant + Bank Dashboard) built with React.js + FastAPI, deployed on Streamlit.
View ProjectHospital SQL Mini Project
February 1, 2026 – February 28, 2026
Designed relational hospital schema covering patients, doctors, appointments and billing records. Wrote complex SQL queries for patient record retrieval, doctor scheduling and revenue analysis.
View ProjectMax Showroom Inventory Analysis
February 1, 2025 – May 31, 2025
Built ML model predicting branch-level restocking needs using sales and stock data. Deployed on public Streamlit for real-time inventory decision support.
View ProjectText Emotions Classification Using Machine Learning
February 1, 2025 – April 30, 2025
Classified emotions (joy, anger, sadness, fear) from text using Naive Bayes and SVM with full NLP preprocessing pipeline. Implemented EDA, feature engineering and model evaluation across multiple classifiers.
View ProjectCultural Fit Analysis
The candidate has a diverse set of projects, including professional, personal, and academic, showcasing initiative and a broad interest in AI/ML applications. The target role of AI Engineer aligns well with their M.Sc. in Artificial Intelligence and project experience. The willingness to relocate also indicates flexibility. The breadth of skills across ML, NLP, RAG, and full-stack development (React.js, FastAPI) suggests a versatile individual who could contribute to various aspects of an AI team.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on end-to-end solutions, from model development to deployment. The variety of projects suggests adaptability and a problem-solving mindset. However, without direct assessment data on soft skills, it's difficult to fully evaluate collaboration, communication, and stress handling.