Akalanka Sakalasooriya is an active, self-learning machine learning engineer with a multi-skilled background and a positive mindset. His objective is to effectively utilize his knowledge and experience in implementing production-level machine learning models and backend systems, while maintaining clean and manageable code. Akalanka has worked with both small and large teams across various projects and companies, demonstrating efficient time management skills. He is capable of working independently in office or remote settings as required.

In his current role as an Associate Machine Learning Engineer at Orel IT, Akalanka is involved in a supermarket shelf management research project. He utilizes technical tools such as YOLO v5, v7 for object detection, PyTorch and EfficientNet B3 for image classification, and Python libraries like Flask, Docker, and AWS EC2 for implementing a production-ready backend. Additionally, he has experience in deploying models using AWS Sagemaker for inference endpoints and training deep learning models with PyTorch and PyTorch Lightning module.

During his previous role as a Trainee Data Science Engineer, Akalanka developed an OCR application using easyOCR, OpenCV, and Tkinter for extracting employee details from images. He also implemented a voice-enabled chatbot using Rasa, Python, Docker, and Flask, as well as worked on a voice similarity checking research project using librosa.

As an Intern Software Engineer at Acentura, Akalanka developed backend AWS lambda APIs using Node.js for attendance, leave management, and report generation systems. He configured AWS Lambda services for triggering email notifications and implemented Bitbucket CI/CD pipelines. Additionally, he managed various AWS services and resources and gained experience in Linux commands, Bash scripts, and containerization.

Furthermore, Akalanka has completed certifications such as Microsoft Certified: Azure Data Scientist Associate (DP-100) and Azure Data Fundamentals (DP-900). He has also pursued courses on containerization technology (Docker), Linux (NDG Linux Unhatched), and exploratory data analysis with Seaborn.

In terms of academic and self-learning projects, Akalanka has implemented a semi-automated Sinhala-English text data annotation tool, developed a movie recommendation and genre prediction web app, created data warehouse components, performed data analysis with Pyspark and HiveQL, deployed a containerized waitress server in a Kubernetes cluster, and developed web apps using microservices architecture.

He holds a BSc (Hons) in Information Technology specializing in Data Science from the Sri Lanka Institute of Information Technology (SLIIT) and has achieved a cumulative GPA of 3.34/4.0. Akalanka was also selected for the SLIIT Dean's list, and his final year research project was chosen for the NBQSA National ICT Awards competition.

Outside of work and academia, Akalanka has been an active member of IEEE and the Mozilla Campus Club of SLIIT. He has also completed a training program on basic aeronautical theory in collaboration with the Sri Lanka Air Force.

In terms of personal skills, Akalanka is result-oriented, motivated to learn, and possesses an analytical mind.