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AI Engineer with less than a year in Machine Learning, Computer Vision, and Predictive Modeling with
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Assessing your cultural and operational fit
Software Engineering undergraduate specializing in Machine Learning, Computer Vision, and Predictive Modeling. Hands-on experience building and deploying end-to-end AI/ML systems using Python, TensorFlow, OpenCV, and Scikit-learn. Proven ability to train, evaluate, and optimize models across classification, regression, and deep learning tasks, with full-stack integration skills to deliver production-ready AI-powered applications.
Sabaragamuwa University of Sri Lanka
BSc (Hons) Software Engineering · Software Engineering
January 1, 2023 – January 1, 2027
Pu/Science High School
G.C.E. Advanced Level · Physical Science Stream
January 1, 2021 – January 1, 2022
LapPredict - Laptop Price Prediction System
January 1, 2023 – June 1, 2026
Developed a Random Forest regression model to estimate laptop prices based on 6+ hardware specifications (brand, RAM, processor, storage, GPU, display), achieving ~75% prediction accuracy on a 1,000+ record dataset. Cleaned and preprocessed 1,000+ raw records using Pandas and NumPy, resolving inconsistencies, encoding categorical variables, and engineering features to improve regression model performance. Created a Flask-based web application for laptop price estimation, delivering predictions in ~1 second through a responsive HTML/CSS interface.
View ProjectStudent Performance Predictor
January 1, 2023 – June 1, 2026
Built a binary classification model using Scikit-learn to predict student pass/fail outcomes, achieving ~92% accuracy across 2+ academic feature categories through iterative hyperparameter tuning. Performed end-to-end data preprocessing and feature engineering handling missing values, encoding 5+ categorical variables, and normalizing numerical features to optimize model input quality. Evaluated model performance using accuracy, precision, and confusion matrix metrics, achieving ~0.5 second prediction time during local testing.
View ProjectATM Guard AI: Real-Time Surveillance System
January 1, 2023 – June 1, 2026
Led a team of 2 members and implemented AI/ML models using TensorFlow and OpenCV, achieving ~80% accuracy; developed a backend processing system for continuous data handling; created a monitoring dashboard for user interaction. Designed an AI-powered surveillance system for ATM security, training on 1,000+ images with data augmentation, achieving ~80% accuracy in threat detection. Engineered 4+ Express.js API endpoints to bridge the Python ML pipeline with the React.js dashboard, delivering real-time threat alerts with under 1-second response latency during live surveillance.
View ProjectInterviewGenie: AI-Powered Interview Assistant
January 1, 2023 – June 1, 2026
Engineered an AI-powered mock interview platform using Gemini AI (~1K token-based requests) to generate questions and deliver instant feedback across multiple sessions. Built a full-stack application using Next.js and Node.js, supporting 10+ interview sessions; integrated Gemini AI for automated question generation; enforced secure authentication for multi-user access. Configured Next.js server-side rendering (SSR) for 3+ core pages, reducing initial load latency and improving responsiveness for concurrent users across varying network conditions.
View ProjectPython for AI & Machine Learning
Udemy
January 1, 2026 – Present
Python for Everyone
Udemy
January 1, 2026 – Present
Introduction to Generative AI
Google Cloud Skills Boost
March 1, 2025 – Present
Web Development
Sololearn
March 1, 2025 – Present
Cultural Fit Analysis
The candidate's project portfolio demonstrates a strong interest and practical application in AI/ML, aligning well with an AI Engineer role. The diversity of projects (surveillance, interview assistant, price prediction, student performance) showcases a broad application of AI concepts. Participation in extracurricular activities and a hackathon indicates a proactive and engaged approach, which generally contributes positively to cultural fit. However, as an undergraduate with no formal work experience, the candidate's exposure to professional team dynamics and corporate culture is limited.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to lead a small team (ATM Guard AI) and participate in group projects, suggesting potential for teamwork. The Hackventure competition semi-finalist status also points to problem-solving and collaborative skills under pressure. However, without direct behavioral assessment, the depth of these soft skills and operational fit remains to be fully validated.