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AI Engineer with less than a year in ML & Data Engineering
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Machine Learning undergraduate with hands-on experience developing and deploying end-to-end ML systems. Skilled in Python, Scikit-learn, PyTorch, PySpark, and MLOps tools including MLflow, Kafka, Airflow, and Docker. Passionate about solving real-world problems using machine learning, deep learning, and data engineering technologies.
University of Colombo
B.Sc. (Hons) in Information Technology and Management · Information Technology and Management
N/A – June 30, 2027
Isipathana College
G.C.E O/L · Mathematics, Science, English
N/A – Present
Isipathana College
G.C.E A/L · Combined Mathematics, Physics, Chemistry
N/A – Present
FraudOps Real-Time Fraud Detection MLOps Pipeline
June 5, 2026 – Present
Built a real-time fraud detection pipeline using Python, PyTorch, Kafka, MLflow, and Streamlit. Designed and trained a custom neural network (FraudNet) on 20,000+ transactions. Implemented Kafka-based live transaction streaming and automated deployment workflows using YAML configurations and Makefile automation.
Market Segmentation using K-Means Clustering
June 5, 2026 – Present
Built a clustering model to segment customers into Budget, VIP, and Loyal profiles using purchasing and demographic data. Applied PCA for visualization and used Elbow Method and Silhouette Analysis to determine optimal clustering performance.
Telco Customer Churn Prediction Pipeline
June 5, 2026 – Present
Developed an end-to-end churn prediction system using PySpark, Kafka, Airflow, and MLflow with an F1-score of 0.75. Automated model training workflows and containerized deployment using Docker.
ETL and Data Pipelines with Shell, Airflow and Kafka
IBM
June 1, 2026 – Present
Introduction to Business Analytics
Tableau
June 1, 2026 – Present
Machine Learning Specialization
DeepLearning.AI
June 1, 2026 – Present
Machine Learning with Apache Spark
IBM
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project portfolio demonstrates a strong interest in practical applications of AI and MLOps, aligning well with a role focused on building and deploying AI solutions. The diversity of projects (fraud detection, churn prediction, market segmentation) shows adaptability and a broad understanding of ML use cases. However, the lack of professional experience means cultural fit is primarily inferred from project initiative and technical alignment, which may require further validation.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive approach to problem-solving and system development. The involvement in extracurricular activities suggests teamwork and leadership potential. However, without direct interview data or psychometric test results, it is difficult to fully assess soft skills like communication, stress handling, and direct team collaboration.