Hi - I'm Alex! I've spent the last 3 years building production AI/ML systems at MSC Industrial Supply (recommendation engines, search relevance, customer segmentation & churn) while completing my MS in Data Science at UNC Charlotte.

I'm also one of two developers for an Agentic AI graduate course at UNC Charlotte which mostly means I get to nerd out about autonomous systems and call it work.

Languages: Python, SQL, R
Cloud: GCP (Vertex AI, BigQuery ML), AWS, Azure
AI/ML: LangGraph, CrewAI, TensorFlow, Scikit-learn, LLMs, Embeddings
Data Engineering: PySpark, Docker, Snowflake, Git

Figuring out how to make AI agents actually useful in enterprise settings (not just cool demos). Most of my day-to-day involves structured and unstructured data at scale (clickstream, product catalogs, customer behavior) and turning that into models that ship. I care about the gap between "it works in a notebook" and "it works in production." That's where the real engineering lives.

Lately I've been deep in the world where embeddings and LLMs meet traditional ML. Think semantic search, recommendations that actually understand context, and agentic workflows as pieces of bigger pipelines instead of just chatbots.

At the end of the day I want to build things that actually help people. Right now that looks like a computer vision app for healthcare I've been developing over the past few months - more coming soon.

• Wrapping up my MS after 4 years of balancing it with full-time work - graduating May 2026
• Building multi-agent systems using both graph-based (LangGraph) and role-based (CrewAI) frameworks
• Training for my first triathlon because apparently training models wasn't enough suffering
• Open to collaborating on interesting ML/AI projects

Most of my production work lives in private repos. The public stuff here is what I'm building on my own time.