:About Cityloix

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

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 and 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