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AI Engineer with less than a year in Machine Learning, NLP, and Full-Stack Development.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
B.Tech graduate in Artificial Intelligence & Data Science with hands-on experience in machine learning, NLP, deep learning, and full-stack development through internships and real-world projects. Proficient in Python, scikit-learn, TensorFlow, Flask, and data analysis, with a strong record of building end-to-end AI applications that deliver measurable business impact.
Rajalakshmi Institute of Technology
B.Tech · Artificial Intelligence and Data Science
January 1, 2022 – January 1, 2026
RD Infro Technologies
Web Development Intern
December 1, 2024 – March 31, 2025
Chennai, Tamil Nadu, India
DLK Technologies
Data Science Intern
June 1, 2024 – August 31, 2024
Chennai, Tamil Nadu, India
AI Resume Screener
June 1, 2026 – Present
Built an ATS-style automated resume screening system using TF-IDF vectorization and cosine similarity to rank candidate-job fit, surface skill gaps, and return a scored match percentage. Trained a logistic regression classifier on 500+ labeled resumes (~82% validation accuracy); deployed as a production-ready Flask web app with a REST API backend.
Cricket Runs Detector
June 1, 2026 – Present
Built a real-time browser-based scoreboard with event-driven DOM manipulation (zero page reloads), fully responsive across desktop and mobile viewports.
DocuBot
June 1, 2026 – Present
Built a Retrieval-Augmented Generation (RAG) chatbot using LangChain and OpenAI GPT-3.5 that ingests PDF/text documents, chunks and embeds content into a FAISS vector store, and answers natural-language queries with cited source passages. Implemented prompt engineering techniques (chain-of-thought, few-shot examples) to reduce hallucination rate by ~40%; deployed as a Flask web app with a REST API supporting multi-document sessions and conversation history.
Predictive Healthcare Analytics
June 1, 2026 – Present
Engineered 35+ clinical features from structured EHR data using pandas and SQL; trained an XGBoost gradient-boosting model achieving 91% ROC-AUC to flag high-risk readmission patients 30 days post-discharge. Integrated SHAP explainability to surface top risk factors per patient and deployed an interactive Streamlit web app that reduced model black-box concerns for clinical staff; demonstrated 18% potential reduction in unnecessary readmissions in pilot testing.
Cultural Fit Analysis
The candidate's project portfolio demonstrates a strong interest and practical application in AI and Data Science, aligning well with an 'AI Engineer' role. The diversity of projects, from NLP-based screening to RAG chatbots and predictive healthcare analytics, shows a broad interest in different AI domains. The inclusion of a web development internship and a basic web app project indicates a willingness to explore different technical areas, which can be a positive for team collaboration and adaptability. However, all projects are personal, and the internships are relatively short, which might limit exposure to larger team dynamics and corporate environments. The candidate is still pursuing a B.Tech degree, indicating an early career stage.
Soft Skills & Operational Fit
The candidate's resume highlights experience in Agile sprint cycles, cross-browser QA testing, proactive blocker flagging, and consistent task delivery, indicating a good operational fit. The mention of 'Problem Solving, Analytical Thinking, Team Collaboration' as technical skills suggests an awareness of important soft skills, though these are not explicitly demonstrated in the provided project descriptions beyond successful project completion.