Senior Machine Learning & Research Engineer · Toronto, ON
I’m a developer and builder—I like to explore a lot of things, break problems apart, and follow ideas from “what does the paper say?” to “does it actually run in prod?”. Research and engineering feel like the same hobby to me: try something, measure it, simplify, repeat.
Most of my ~10 years in the field have been at the messy intersection of ML, data, and product. Lately that’s meant Gen AI, RAG, LangGraph, and multi-agent workflows in regulated finance; before that, similar puzzles at GCash, Unionbank, and earlier analytics roles. I care about the craft—clean libraries, sharp retrieval, fairness and privacy when models touch real people.
When I’m not heads-down at work, I’m usually tinkering in public repos, blogging experiments on my site, or spiraling on a new stack I probably don’t need but want to understand anyway.
Languages & data
ML / DL / NLP
Gen AI, agents & APIs
Cloud, data & MLOps
Also in heavy rotation: vector search (Azure AI Search, FAISS, Pinecone, Annoy), Cosmos DB, MLflow, Power BI, evaluation (RAGAS, Deepeval), and responsible-AI tooling (Fairlearn, IBM AIF360).
Most of the interesting stuff ends up on GitHub or the blog—thanks for visiting.