Lyft
Software Engineering Intern
2026
Software engineering / ML systems / AI tooling
I build software around machine learning: product surfaces, backend systems, data pipelines, evaluation tooling, and agentic workflows.
Summary
I'm a software engineer working in developer tooling, Machine Learning, and agent infrastructure, currently completing a double degree in Mathematics and Business Administration at the University of Waterloo and Wilfrid Laurier University.
My experience spans data engineering and applied AI. I've built real-time data pipelines and cloud migrations at theScore, RAG features and LLM evaluation systems at Borealis AI, and agent tooling at Lyft — including a Python MCP server and an AI agent that autonomously authors, deploys, and debugs production workflows.
I'm drawn to problems where automation meets reliability: static analysis, evaluation frameworks, audit and observability layers, and human-in-the-loop system design. Building software that acts on its own is increasingly straightforward; building it so its actions can be verified, constrained, and trusted is the harder and more interesting problem.
Outside of work, I run, play hockey, and spend most of my free time being active.
Experience
Software Engineering Intern
2026
Machine Learning Software Engineering Intern
2026
Data Engineering Intern
2024 - 2025
Nuclear Data Operations Intern
2024
Data Engineering Intern
2023
Tools