Computer Vision Engineer — Structural Inspection
We are building a robotic system for automated structural inspection of bridges and tunnels. Our sensor package combines LiDAR, structured light, and high-resolution cameras. The vision pipeline processes data from all three modalities to detect surface cracks, spalling, and deformation — defects that currently require a person to abseil down a bridge or crawl through a tunnel with a flashlight and a clipboard. We are pre-revenue. We have completed inspections on four structures under contract with two state DOTs as proof-of-concept engagements. We have $2.1M in grant funding from ARPA-E and a Series A process that we expect to close in Q3. We are telling you this because you deserve to know the risk profile of the company you're joining. This is early, there is risk, and the equity reflects that. What we have is a genuinely hard vision problem, a physical system that works well enough to inspect real infrastructure, and a small team of people who are serious about solving it properly. The vision work involves multi-modal fusion, 3D point cloud processing, and crack detection on textured concrete surfaces — not a clean benchmark dataset.