Experience
Mechanical Engineer Co-op
ColdSnap
January 2025 — July 2025
At ColdSnap, I worked across the full lifecycle of a complex consumer appliance: designing, manufacturing, and verifying components, then managing reliability and life testing of the electromechanical assemblies against internal standards. The role required constant collaboration with cross-functional engineering teams to make sure component designs stayed aligned with both production feasibility and performance goals.
A recurring theme in my work was turning hands-on problems into practical tools: I processed and organized large volumes of test data into reports that directly guided production and user-experience decisions, and I designed and 3D-printed a dedicated circumference gauge to solve a calibration problem on the manufacturing line that eventually became part of the standard process. I also contributed to a team project optimizing the appliance's chilling cycle, varying spin rate over time to find the fastest freeze profile without sacrificing texture.
Project Engineer Intern
PROTECs
May 2026- August 2026
At PROTECS, I worked on cost estimation for life sciences facility construction projects, performing material takeoffs of ductwork, flooring, wall systems using Procore and Bluebeam to translate design documents into accurate project costs. Working within a 4-person project team, I supported the broader construction management workflow for clients in a highly regulated industry where accuracy in estimating directly affects project budgets and timelines.
Beyond takeoffs, I led an internal research initiative evaluating how AI tools could improve cost estimating, scheduling, and document review — an area with no established playbook at the company yet. I had to figure out which tools were actually relevant to construction workflows versus general-purpose hype, test them against real project scenarios, and distill the findings into something project leadership could act on. I presented my findings directly to leadership, giving them a clearer picture of where AI could realistically save time versus where it fell short for the team's day-to-day work.