I’m a machine learning engineer focused on Recommendation Systems and the tools that make them useful.

I’m especially interested in large language models, inference, practical AI infrastructure, and turning research ideas into reliable products.

This site is where I document what I’m learning, ideas I’m testing, and the occasional thought about life.

Some things I write about:

• Building and evaluating applications with LLMs
• Retrieval, caching, and in-context learning
• ML tools, engineering tradeoffs, and lessons from experiments
• Technology, decision-making, and the craft of getting better

Read the full archive in [blogs].