About Me
I'm an MLOps Engineer focused on building and optimizing scalable machine learning infrastructure. I specialize in designing efficient ML pipelines, implementing robust CI/CD workflows, and developing cloud-native solutions that ensure seamless model deployment and monitoring.
Academic Background
Master's Degree
Master's in Computer Science with focus on Machine Learning and Artificial Intelligence
Publication
Stock Market Prediction: Integrating Explainable AI with Conv2D Models for Candlestick Image Analysis
Published in WorldCIST 2024 Conference Proceedings, Lecture Notes in Networks and Systems
View PublicationAreas of Expertise
MLOps
Building and optimizing scalable ML pipelines, with extensive experience in GitHub Actions for automated testing, deployment, and ML workflow orchestration.
Cloud Computing
Deploying and managing applications on cloud platforms, implementing containerization with Docker, and orchestrating with Kubernetes.
CI/CD Specialist
Expert in GitHub Actions workflows, automating ML model deployment pipelines, and implementing robust continuous integration and delivery practices.
Machine Learning
Developing and deploying ML models with automated training and evaluation pipelines, focusing on reproducibility and scalability.
System Integration
Connecting and optimizing systems across different platforms, implementing efficient data pipelines and automated workflows.
API Development
Creating robust FastAPI endpoints and RESTful services, with automated testing and deployment through GitHub Actions.
Personal Infrastructure
Personal Kubernetes Cluster
A self-managed 7-node Kubernetes cluster running on bare metal, featuring 1 master node and 6 worker nodes. This setup demonstrates hands-on experience with container orchestration and infrastructure management.