About
I build the infrastructure that turns raw data into systems that run without you.
Data scientist turned systems engineer. I got into AI infrastructure because I kept seeing the same problem — creators and media businesses sitting on incredible data with no way to make it useful. So I started building it.
Background
Before building AI systems for creators, I spent [X] years working across data science, data engineering, and machine learning engineering — building production pipelines, training and deploying models, and designing the infrastructure that makes data actually useful at scale.
I've worked in [industry placeholder] and [industry placeholder], where the problems were always the same: teams sitting on valuable data with no reliable way to extract insight from it. The difference between a notebook experiment and a system that runs unsupervised every day is where I spend most of my time.
Roles
Data Scientist
Statistical modeling, experiment design, insight extraction from complex datasets
Data Engineer
Production pipelines, ETL architecture, data infrastructure at scale
ML Engineer
Model training, deployment, embeddings, clustering, and NLP systems
AI Systems Engineer
End-to-end autonomous systems — from ingestion to insight to action
Currently
Focus
AI systems for the creator economy
Building
Production pipelines, audience intelligence tools, and agent systems
Stack
Full detailsLanguages
Data & ML
Databases
Infrastructure
Orchestration
Frontend
Who I work with
Creators and media businesses who are serious about building systems — not just trying tools. If you're looking for someone to set up ChatGPT, I'm probably not the right fit. If you want production infrastructure that runs while you sleep, let's talk.
See how I work