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AI Engineer with less than a year in Machine Learning and Deep Learning
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Assessing your cultural and operational fit
Passionate AI/ML Engineer and Python Developer with expertise in building scalable, intelligent systems. I bring advanced skills in Machine Learning, Deep Learning, NLP, and Generative AI, combined with proficiency in frameworks like TensorFlow, Keras, FastAPI, Flask, Django, and LangChain. I deliver solutions that enhance automation, optimize workflows, and enable data-driven decision-making. My ability to design robust architectures and develop innovative applications positions me to create measurable value and solve complex industry challenges.
SLIIT (Sri Lanka institute Of Information Technology)
BSc (Hons) · Information Technology Specializing in Data Science
August 1, 2023 – June 30, 2027
LangGraph Agentic AI
June 1, 2026 – Present
Developed a modular AI agent system using LangGraph framework featuring an intelligent chatbot with tool integration and automated AI news aggregator. Implemented state management, conditional routing, and dynamic graph construction with Groq LLM backend. Integrated Tavily search API for real-time data retrieval and built an interactive Streamlit UI. Automated content summarization pipeline for daily/weekly/monthly AI news briefings.
View ProjectPotato Disease Detection System
June 1, 2026 – Present
Engineered an end-to-end deep learning solution for identifying potato leaf diseases (Early Blight, Late Blight, Healthy) using a custom Convolutional Neural Network (CNN) with TensorFlow/Keras. Focused on data preprocessing, data augmentation to mitigate overfitting, and deployed the inference API using FastAPI for real-time predictions.
View ProjectRAG with Chat History - Conversational Document QA System
June 1, 2026 – Present
Built a Retrieval Augmented Generation system using LangChain and Groq LLM for contextual PDF conversations with persistent chat history. Implemented history-aware retrieval with Chroma vector store and HuggingFace embeddings. Developed a Streamlit interface with multi-PDF upload support and session-based conversation management using RunnableWithMessageHistory for intelligent follow-up questions.
View ProjectSpotify Popularity Predictor
June 1, 2026 – Present
Designed and deployed a Random Forest machine learning pipeline (Scikit-Learn, Streamlit) to predict Spotify track popularity based on mathematical sonic features. Cleaned and deduplicated a 114k-row dataset, engineering 113 granular genres down to 15 broader categories to prevent data leakage and model overfitting.
View ProjectChat-SQL FastAPI - Natural Language Database Query System
June 1, 2026 – Present
Built a FastAPI + LangChain API for natural language SQL queries with session-based chat, Groq LLM integration, and structured responses for seamless frontend use.
View ProjectMachine Learning Fundamental of Python
UDEMY
June 1, 2026 – Present
Mastering Python, Pandas, NumPy
UDEMY
June 1, 2026 – Present
Intro To Deep Learning
KAGGLE
June 1, 2026 – Present
Intro To Machine Learning
KAGGLE
June 1, 2026 – Present
Complete GenAI with Langchain & HuggingFace
UDEMY
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project portfolio demonstrates a strong interest and proactive approach to learning and applying cutting-edge AI technologies. The diversity of projects, ranging from disease detection to conversational AI and agentic systems, indicates a broad curiosity and willingness to tackle different problem domains. This aligns well with a dynamic, innovation-driven culture. The self-driven nature of personal projects suggests initiative and a passion for the field, which are positive cultural indicators. However, without team-based project experience or direct behavioral assessment, the extent of their collaborative cultural fit is not fully ascertainable.
Soft Skills & Operational Fit
The candidate lists several soft skills including verbal and written communication, adaptability, teamwork, leadership, empathy, and professionalism. While these are positive attributes, there is no direct assessment data to validate their proficiency in these areas. The project descriptions suggest an ability to work independently on complex tasks, which is a good indicator for operational fit in a technical role.