About
Building ML Systems That Work
This blog documents my journey in making ML systems reliable, scalable, and actually useful in production. Expect stories of both triumphs and failures, always with concrete takeaways.
At Trontal Group, I architect infrastructure for quant trading and ML systems, after working at the Machine Learning Labs at MoneyLion.
My focus? Making machine learning work reliably at scale - from serving LLMs to building MLOps platforms used by dozens of data scientists.
Teaching & Writing
When not in the trenches, I share what I’ve learned. I’ve taught 1500+ students globally about scaling ML systems and DevOps practices. My writing covers the unvarnished reality of production ML - no hype, just hard-earned lessons.