AI Engineer

The objective is to develop an AI model that detects and classifies Longitudinal and Transverse Cracking (LTC) in asphalt airfield pavements, in accordance with ASTM D5340-24. The model will use fused Digital Elevation Model (DEM) and imagery data to identify cracks, measure their extent, and assign a severity level (Low, Medium, or High) based on the standard's width and spalling criteria. The output will support the broader Pavement Condition Index (PCI) workflow used across the company's 85-model system. What you'll need to do: • Access and understand the provided DEM and imagery data, along with existing labels • Build a pipeline that fuses DEM and imagery to detect cracks and measure their length and width • Train a model to classify each detected crack as Low, Medium, or High severity per the ASTM thresholds • Apply the standard's exclusion rule so distresses are not double-counted where other cracking is already recorded • Validate the model's outputs against the team's verified ground truth and report accuracy • Deliver the trained model along with a short write-up of results and any limitations