Spotlight

Research, writing, and technical contributions at the intersection of applied ML, systems engineering, and rigorous problem-solving.

I'm a senior engineer specializing in AI systems — Python services, agent pipelines, and the infrastructure that makes LLM applications reliable at scale. My background spans distributed systems, ML tooling, and applied research, with a track record of taking complex AI ideas from prototype to production.

On the research side, I work on interpretable AI, LLM evaluation, and techniques for reducing technical debt in ML codebases. My published work on genetic algorithms for community detection reflects a longer interest in systems that produce understandable, auditable outputs — a concern that has only become more relevant as LLMs move into critical workflows.

The throughline is impact: tools and systems that help teams ship faster, debug more confidently, and maintain AI-driven products without heroics. I care about work that scales beyond the person who built it.