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AI Engineer with less than a year in Python, Machine Learning, and NLP.
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Final-year B.Sc. Artificial Intelligence student (CGPA 8.20) with hands-on experience in Python, Machine Learning, NLP, and SQL. Completed an AI & ML internship at VDart and independently built 4 end-to-end projects including an NLP chatbot, a natural language-to-visualization system, and a self-evolving multi-agent AI framework. Proficient with scikit-learn, TensorFlow, Pandas, NumPy, and AWS. Seeking a software development, data analysis, or AI/ML role to deliver measurable business value.
Periyar Maniammai Institution of Science & Technology
B.Sc. Artificial Intelligence · Artificial Intelligence
August 1, 2023 – June 30, 2026
AJC Public School
HSC – Class XII (CBSE)
June 1, 2022 – May 31, 2023
AJC English School
SSLC – Class X (CBSE)
June 1, 2020 – May 31, 2021
VDart
AI & ML Intern
June 1, 2024 – June 30, 2024
Tiruchirappalli, Tamil Nadu, India
AI Chatbot (NLP-based)
January 1, 2024 – June 30, 2026
Built a rule-based intent classification chatbot using TensorFlow and NLP techniques (tokenization, lemmatization, bag-of-words), handling 15+ intent categories with 88% accuracy. Trained and evaluated the model end-to-end — from data preparation to deployment — demonstrating a complete ML workflow in under 2 weeks solo.
View ProjectSelf-Evolving Multi-Agent System (SEMAS)
January 1, 2024 – June 30, 2026
Architected a 5-agent autonomous framework (Orchestrator, Planner, Executor, Evaluator, Reflector) capable of executing and adapting to complex tasks without human intervention. Implemented a Self-Evolution Engine using reinforcement learning to optimize agent policies iteratively, improving task success rate by ~25% across 100+ training episodes. Built a real-time Streamlit dashboard visualizing agent status, training progress, and KPIs; reduced debugging time by 40% through live metric monitoring. Engineered shared memory and inter-agent communication layer, enabling agents to collaborate on tasks with 3x faster convergence compared to isolated execution.
View ProjectNL2VIZ — Natural Language to Visualization Library
January 1, 2024 – June 30, 2026
Engineered an NLP-powered system that translates plain-English queries into accurate charts and graphs, supporting 8+ chart types (bar, line, scatter, pie, heatmap, etc.). Applied text parsing and intent classification techniques using spaCy and regex, achieving 90% query-to-chart mapping accuracy on a test set of 200 queries. Reduced manual data visualization effort by 60%, enabling non-technical users to generate insights without writing any code.
View ProjectStudent Data Dashboard
January 1, 2024 – June 30, 2026
Developed a responsive front-end dashboard to display, filter, and search student records dynamically from a 500+ row SQL database. Reduced data retrieval time by 50% compared to manual lookups via optimized SQL queries with indexed columns and JOIN operations.
View ProjectPython Basics for Data Science
IBM / Coursera
January 1, 2024 – Present
TensorFlow Developer Fundamentals
DeepLearning.AI / Coursera
January 1, 2024 – Present
AI & ML Internship Completion Certificate
VDart, Trichy
January 1, 2024 – Present
Cultural Fit Analysis
The candidate's academic projects show a strong interest in diverse AI applications, from NLP chatbots to multi-agent systems and data visualization. This breadth of interest aligns well with an innovative and research-oriented culture. The mention of Agile sprint workflows during the internship suggests adaptability to structured development environments. The candidate's focus on practical application and measurable outcomes (e.g., accuracy improvements, time reduction) indicates a results-oriented mindset.
Soft Skills & Operational Fit
The candidate demonstrates initiative and self-direction through independently built projects. The internship experience suggests an ability to work within a team and adhere to Agile workflows. The project descriptions indicate a focus on problem-solving and improving efficiency (e.g., reducing debugging time, faster convergence).