AI Engineer with less than a year in Machine Learning and Analytics.
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Highly motivated and results-oriented Data Science and AI Engineer pursuing a B.E. in Artificial Intelligence and Machine Learning. Possessing 2 months of internship experience in data processing, visualization, and predictive modeling. Proficient in Python, TensorFlow, Keras, and various AI/ML frameworks like LangChain. Demonstrated ability to deliver impactful projects, including an explainable multi-agent framework for diabetes decision support and a plant leaf disease detection system.
Chaitanya Bharathi Institute of Technology
B.E · Artificial Intelligence and Machine Learning(AIML)
January 1, 2022 – January 1, 2026
Proxenix
Data Science and Analytics Intern
June 1, 2025 – August 31, 2025
India
DiaGen: Explainable Multi-Agent Framework for Diabetes Decision Support
September 1, 2025 – June 1, 2026
Built a RAG-powered multi-agent clinical decision support system for Type 2 Diabetes using LangChain, FAISS, and Mistral LLM. Designed a 3-agent diagnostic pipeline achieving 100% diagnostic accuracy with zero hallucination across 15 synthetic patient reports.
Plant Leaf Disease Detection using Deep Learning
September 1, 2024 – August 31, 2025
Developed an ensemble deep learning model to classify 38 plant leaf diseases using the PlantVillage dataset with ~90% accuracy. Integrated LIME-based explainable AI for interpretable prediction analysis and diagnosis transparency. Optimized transfer-learning architectures, achieving 86% validation accuracy.
Hospital Management System
September 1, 2024 – August 31, 2025
Developed a full-stack hospital management system with patient registration, appointment scheduling, and admin management modules. Built responsive UI components using Next.js, TypeScript, and Tailwind CSS with optimized routing and state handling. Integrated backend services and database workflows using Appwrite for authentication and data management.
Oracle Cloud Foundations Associate
Oracle
June 1, 2026 – Present
DiaGen: An Explainable Multi-Agent Framework for Automated Diabetes Decision Support
IEEE I3CTCON
January 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a strong interest and foundational skill set in AI/ML, aligning well with an AI Engineer role. The diversity of projects, from medical decision support to plant disease detection and a full-stack system, shows a broad technical curiosity. The internship experience in data science further enhances their practical exposure. However, the candidate is still early in their career (expected graduation 2026), which means their experience is primarily academic. This might require more mentorship and ramp-up time in a professional setting compared to a candidate with more industry experience.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex technical challenges and deliver functional systems. The academic background in AIML and participation in hackathons suggest a proactive and learning-oriented attitude. However, without specific behavioral assessment data, it is difficult to fully assess soft skills like teamwork, communication, and problem-solving under pressure.