Most people see data as a rearview mirror. I see it as a GPS.
I’m a Machine Learning Engineer who enjoys the "boring" parts of AI like making sure models actually stay running in production just as much as the "shiny" parts, like building multi-agent systems that think for themselves.
I live at the intersection of Lakehouse Architectures and Generative AI. Whether it’s orchestrating complex data flows with Airflow and Kafka or building autonomous teams of agents using LangGraph, CrewAI, and AutoGen, my goal is the same: turning raw noise into automated, scalable intelligence.
What I bring to the table:
The Brains: Deep Learning, NLP, and fine-tuning LLMs to do more than just recite poetry.
The Backbone: MLOps, Snowflake, BigQuery, and SQL—because a model is only as good as the data pipeline feeding it.
The Vision: Turning complex datasets into "aha!" moments via Tableau and Power BI.
I don’t just build AI; I build AI that solves business problems without needing a nap.
