Pavement Visual Inspection Engineer

We are hiring a Pavement Visual Inspection Engineer to join our Pavement Assessment team.

This is a hands-on, detail-driven role at the centre of our data quality chain. You will spend most of your time in imagery — labelling pavement distresses, correcting the output of our AI detection models, and performing structured visual inspection on assigned road networks. Your work directly shapes two things at once: the condition data we deliver to clients, and the training datasets that make our models better on the next project.

This role suits someone who takes genuine satisfaction in getting the call right, holds a standard consistently over thousands of segments, and would rather flag a hard case than guess at it.

CORE RESPONSIBILITIES

• Work within the annotation and labelling team to expand and refine model training datasets and deliverable data

• Validate AI-generated defect detections against source imagery — confirming, correcting, or rejecting each output per the assignment criteria

• Identify and classify pavement distresses by type, severity, and extent in accordance with internal guidelines

• Visually review collected pavement-view roadway imagery to assess surface condition across assigned project areas

• Perform independent visual inspection on statistically sampled road segments

• Assess surface type classification (asphalt, concrete, gravel, composite) and confirm the correct defect taxonomy is applied for each surface

• Review segment-level condition scores for consistency with the underlying imagery and defect record

• Detect and report imagery quality issues — occlusion, glare, motion blur, water or snow coverage, insufficient lighting — that prevent reliable assessment