About
I have always been passionate about technology and have been fascinated by the endless possibilities it brings. From a young age, I have been tinkering with computers and have enjoyed learning about the world around me and how tech can be used to solve problems. That curiosity eventually led me to a degree in statistics and a career that's taken me from building ML pipelines at SAS and Collibra to designing MLOps platforms at Booz Allen, and now to the frontier work I'm doing at Seekr.
As a Senior AI Solutions Engineer at Seekr, I work at the intersection of model development and the infrastructure that has to run it safely and reliably. What that looks like day-to-day is below.
Outside of work, I keep building — recent side projects have pushed me further into full-stack territory with Vue and React, deployed on Vercel. Shipping something real is still the fastest way I know to test whether an idea actually holds up.
What I'm Currently Building
Fine-tuning Foundation Models
Closing the gap between a general-purpose model and one that actually understands a specific domain well enough to trust.
Sovereign AI & GPU Infrastructure
Designing for environments where data never leaves the building and every dependency has to be accounted for.
Agentic AI Architectures
A system that takes action on its own only earns that trust once you can show it acts correctly, consistently.
Model Explainability & Evaluation
The unglamorous work that determines whether anything above this line can actually be relied on in production.
LLMOps / MLOps
Getting a model from 'it works on my machine' to something that serves real traffic reliably.
Infrastructure as Code
Every deployment reproducible and auditable — no snowflake environments, no tribal knowledge.
Outside of work: running and hiking trails, cooking, and biking around the DC area — which also offers easy access to public transit for exploring both the city and the outdoors.
Let's Connect!
Interested in chatting about AI, infrastructure, or potential opportunities?