ABOUT CITYLOGIX Citylogix builds AI-driven infrastructure data collection and condition assessment programs for municipal clients across North America. Our crews collect roadway imagery at scale; our processing pipeline turns that imagery into defensible pavement condition data that cities use to plan and defend capital programs. The accuracy of that data depends on people who can look at a road surface and call it correctly, every time. ABOUT THE ROLE 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 QUALIFICATIONS — REQUIRED Bachelor's degree in Civil Engineering, Transportation Engineering, or a related discipline Strong visual attention to detail, with the ability to maintain consistency across high-volume repetitive review Comfort working for extended periods within image-review software environments Ability to apply written standards consistently and document deviations clearly Strong written and verbal communication skills in English ATTRIBUTES & WORKING STYLE Methodical and consistent — able to make the same judgment call Comfortable operating within defined standards, and flags genuine edge cases rather than guessing Collaborative approach to feedback, both giving and receiving Ownership mindset toward deliverable quality