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AI Engineer with less than a year in Generative AI & Machine Learning
AI/ML Engineer with hands-on experience in designing, training, and deploying machine learning and deep learning solutions, including Generative AI systems using OpenAI and Gemini APIs, Retrieval-Augmented Generation (RAG), and FAISS-based vector databases. Strong background in computer vision, natural language processing, and building scalable AI applications using Python, PyTorch, TensorFlow, FastAPI, WebSockets, and AWS. Skilled in optimization techniques such as genetic algorithms and meta-learning, as well as knowledge representation using ontology tools. Known for strong problem-solving abilities, a collaborative mindset, and a passion for continuous learning, seeking a full-time AI/ML Engineering role to contribute to impactful AI-driven solutions.
University of Moratuwa
BSc (Hons) in Artificial Intelligence · Artificial Intelligence
August 1, 2022 – June 30, 2026
J/Vayavillan Central College
G.C.E. Advanced Level
June 1, 2018 – May 31, 2020
Prime Technologies
Junior AI/ML Engineer
February 1, 2025 – August 1, 2025
Sydney, New South Wales, Australia
Meta Learning Engine for Trading
December 1, 2025 – February 1, 2026
Implemented a Meta-Learning Engine for trading systems using genetic algorithms and clustering techniques to enable adaptive strategy learning. Developed and exposed FastAPI endpoints for model interaction, data processing, and strategy evaluation. Designed and integrated Cron jobs and cache storage mechanisms to support scheduled learning cycles and efficient data access. Built the Adaptive Learning component of the engine to dynamically update trading strategies based on evolving patterns. Tested API endpoints, deployed the application on Render, and continuously monitored performance to identify and fix bugs.
Fuzzy Attention Transformer for Uncertainty-Aware Brain Tumor Segmentation
July 1, 2025 – July 1, 2026
Designed a hybrid Fuzzy Attention Transformer by integrating fuzzy membership functions into TransUNet, replacing binary attention with membership-based scoring to model uncertainty in diffuse brain tumor regions. Trained and evaluated the model on the BraTS multi-modal MRI dataset, generating segmentation masks and uncertainty maps and improving boundary sensitivity, validated using Dice Score, HD95, and ECE.
Vehicle Detection and Classification using SSD with VGG-16 Backbone
February 1, 2024 – February 1, 2024
Method for vehicle detection and classification using the Single Shot MultiBox Detector (SSD) model with a VGG-16 backbone. Model is trained on a custom dataset with vehicle categories including: Auto, Bus, Car, LCV, Motorcycle, Truck, Tractor, Multi-Axle Data augmentation techniques and transfer learning are employed to improve model performance. The method achieves high accuracy in detecting and classifying vehicles. Provides a robust solution for traffic monitoring and analysis.
SentiView - Collaborated with CodeGen
January 1, 2024 – March 1, 2025
Developed a user-friendly dashboard to visualize customer sentiment by collecting and processing data from various sources and integrating it via API. Implemented real-time data visualization, a notifications API and managed the entire data flow for seamless sentiment analysis.
GenpptX - Presentation Generator(Gemini AI)
January 1, 2024 – March 1, 2024
Developed a platform utilizing Gemini AI's API to create customizable PowerPoint presentations. Users can input topics, select from various templates, and download personalized presentations with ease.
View ProjectFace Detection and Proximity Indicator
January 1, 2023 – December 31, 2023
This project aims to detect faces in group images and identify individuals whose faces are in close proximity to each other. It utilizes face detection techniques to locate faces and calculates the distance between the centers of detected face rectangles to determine proximity.
View ProjectReal-Time Face Recognition and Attendance and anonymous Tracking
January 1, 2022 – December 31, 2022
This system uses facial recognition to log employee attendance in an Excel sheet with timestamps and it stores images of unknown individuals or employees entering outside office hours in separate files, enhancing both convenience and security.
View ProjectStamp calculator Machine
January 1, 2022 – December 31, 2023
Developed as a university project, this machine calculates postage and dispenses stamps based on mail weight, providing a streamlined and efficient solution for postage management.
View ProjectNeural Networks and Deep Learning
DeepLearning.ai - Coursera
June 1, 2026 – Present
Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization
DeepLearning.ai - Coursera
June 1, 2026 – Present
Structuring Machine Learning Projects
DeepLearning.ai - Coursera
June 1, 2026 – Present
Convolutional Neural Networks
DeepLearning.ai - Coursera
June 1, 2026 – Present
Sequence Models
DeepLearning.ai - Coursera
June 1, 2026 – Present
Introduction to TensorFlow for Artificial Intelligence, Machine Learning and Deep Learning
DeepLearning.ai - Coursera
June 1, 2026 – Present
Convolutional Neural Networks in TensorFlow
DeepLearning.ai - Coursera
June 1, 2026 – Present
Machine Learning with Python
IBM - Coursera
June 1, 2026 – Present
Introduction to Deep Learning & Neural Networks with Keras
IBM - Coursera
June 1, 2026 – Present
Introduction to Computer Vision and Image Processing
IBM - Coursera
June 1, 2026 – Present
Deep Neural Networks with PyTorch
IBM - Coursera
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from academic research to personal and professional projects, indicates a broad interest and adaptability. The involvement in hackathons and extracurricular activities suggests a team-oriented and engaged individual. The target role of AI Engineer aligns well with the candidate's academic background, professional experience, and project portfolio, particularly in Generative AI, RAG, and scalable AI application development.
Soft Skills & Operational Fit
The candidate demonstrates a collaborative mindset and strong problem-solving abilities through project descriptions. The experience with developing a machine learning model training portal and architecting a ride-hailing application suggests an operational fit for MLOps and scalable system design. The continuous learning aspect, highlighted by numerous certifications, indicates a proactive and adaptable individual.