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AI Engineer with 1+ years in Python, Machine Learning, and Generative AI.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Computer Science Engineering graduate skilled in Python, Machine Learning, and Generative AI, with hands-on experience building end-to-end AI applications including Retrieval-Augmented Generation (RAG) systems using LangChain, vector databases, and Large Language Models. Proficient in data preprocessing, feature engineering, model development, and deploying interactive AI solutions using Streamlit. Passionate about developing scalable, data-driven AI systems and contributing to real-world intelligent applications.
Rajadhani Institute of Engineering and Technology
B.Tech · Computer Science and Engineering
August 1, 2021 – June 30, 2025
St. John's School, Anchal
Higher Secondary Education · Computer Science
June 1, 2019 – May 31, 2021
Luminar Technolab
Data Science Intern
July 1, 2025 – March 1, 2026
Thiruvananthapuram, Kerala, India
AI Trip Planner using RAG
June 27, 2026 – Present
Built an AI-powered trip planner using LangChain and vector database to retrieve relevant travel information from PDF datasets. Implemented a complete RAG pipeline including document loading, text chunking, embedding generation, and semantic search for accurate context retrieval. Integrated a Large Language Model (GroqAI) and developed a Streamlit interface to provide real-time, context-aware travel recommendations.
View ProjectCalories Burned Prediction System
June 27, 2026 – Present
Built an end-to-end machine learning system to predict calories burned using workout and user data. Applied feature engineering and One-Hot Encoding, and trained a Random Forest regression model for accurate prediction. Developed an interactive Streamlit application for real-time calorie prediction with dynamic workout selection.
Medi Sense: Smart Medication Management with Health and Emotion Monitoring
June 27, 2026 – Present
Developed an IoT-based smart medication management system with real-time health and emotion monitoring. Designed a smartwatch prototype to track heart rate, oxygen level, and stress indicators. Implemented adaptive medication reminders and caregiver alerts for improved patient support.
Cultural Fit Analysis
The candidate's projects demonstrate a strong interest in applying AI to diverse real-world problems (trip planning, health monitoring, calorie prediction). This aligns with an innovative and problem-solving culture. The listed soft skills (teamwork, adaptability) are generally positive for cultural fit. However, the candidate is still pursuing a B.Tech degree, and their experience is primarily academic/personal projects with one internship, which might indicate a need for mentorship in a fast-paced industry environment. The breadth of skills across ML, DL, and Generative AI suggests a willingness to learn and adapt to new technologies.
Soft Skills & Operational Fit
The candidate lists leadership, quick learning, teamwork, and adaptability as soft skills. The project descriptions suggest an ability to work independently on complex tasks. The internship experience indicates exposure to a professional environment and collaboration on data science tasks. However, without direct interview data, the operational fit and depth of these soft skills cannot be fully assessed.