About Me
I am a seasoned technology professional with a strong foundation from my MS in IT, specializing in enterprise architecture and robust system design. My current focus is on bridging the gap between infrastructure scaling and data science as I pursue my Masters in AI.
My core expertise lies in DevOps Engineering, where I architect and automate highly available, scalable, and secure cloud environments (CI/CD, Infrastructure as Code).
The AI studies allow me to bring a critical MLOps perspective to my engineering, ensuring that machine learning models are not just built, but deployed, monitored, and maintained efficiently in production. I thrive at the intersection of reliable systems and cutting-edge data science.
My Value Proposition
- Scalable Infrastructure: Expertise in Terraform, Kubernetes, and Cloud platforms (AWS/GCP) for high-performance systems.
- AI Deployment: Focusing on MLOps, CI/CD for models, and data pipeline reliability.
- Dual Master's Insight: Bringing advanced knowledge from both IT management and pure AI research.
Technical Toolkit
DevOps & Cloud Engineering
AI, ML, & MLOps
Programming & Databases
Key Projects
A selection of demonstrating my capability in both scalable infrastructure and intelligent systems.
Full-Stack MLOps Pipeline on GCP
DevOps / AI
Automated CI/CD pipeline for deploying a neural net model to Google Kubernetes Engine (GKE) using Terraform for infrastructure provisioning and Kubeflow for workflow orchestration.
View CodeTerraform Multi-Cloud Module
DevOps / IaC
Designed and implemented reusable Terraform modules for VPC, compute, and networking across AWS and Azure, reducing infrastructure deployment time by 40%.
View CodeMasters AI Thesis: LLM Fine-Tuning
AI / Research
Research and prototype focusing on fine-tuning small, open-source Large Language Models (LLMs) for domain-specific tasks using LoRA methods and Pytorch.
View Paper/CodeAcademic Background
Master of Science in Artificial Intelligence
University of the Cumberlands
Relevant Coursework: Deep Learning, MLOps, Statistical Modeling, Big Data.
Master of Science in Information Technology
University of the Cumberlands
Focus: Enterprise Systems, Cloud Computing Fundamentals, Project Management.