Are you a pavement professional or roadway inspector with hands-on experience conducting or interpreting Pavement Condition Index (PCI) surveys? Advanced AI systems are being developed to understand roadway conditions, interpret inspection imagery, and support infrastructure maintenance planning. High-quality training data based on real PCI survey practices is essential to ensure these systems accurately recognize pavement distress and condition ratings. This project relies on your expertise to help train and evaluate next-generation AI models.
In this project, you will focus specifically on PCI-related workflows and annotation tasks. You will review roadway images, inspection records, and AI-generated outputs to determine whether pavement distress types, severity levels, and condition assessments are accurate and consistent with PCI methodology. A central part of the work involves annotating or validating pavement features and distress patterns so models can better learn to identify cracking, rutting, spalling, patching, weathering, and other common pavement conditions.
On a typical day, you may analyze roadway imagery or survey excerpts, validate AI-generated classifications of pavement distress, and provide written feedback explaining where models misidentify features or misinterpret severity levels. You may also help clarify how inspectors distinguish between similar distress categories, how sampling units are evaluated, and how real-world field conditions influence PCI scoring and reporting.
This project is well suited for pavement engineers, civil or transportation engineers, DOT specialists, highway inspectors, and other professionals who have conducted or reviewed PCI surveys or pavement condition assessments. Experience working with inspection imagery, condition reports, or roadway maintenance planning is highly valuable. Clear written communication and the ability to explain inspection reasoning and classification decisions in a structured way are essential.
No prior AI or technical background is required. Training and project guidelines will be provided. What matters most is your familiarity with PCI surveys, attention to visual detail, and ability to consistently apply pavement distress definitions and rating criteria.
We offer a pay range of $6 - $20 per hour, with the exact rate determined after evaluating your experience, expertise, and geographic location. Final offer amounts may vary from the pay range listed above. As a contractor, you will supply a secure computer and high-speed internet; company-sponsored benefits such as health insurance and PTO do not apply.
Job title: Pavement Condition Index (PCI) Survey & Annotation Specialist – Freelance AI Trainer Project Employment type: Freelance / Contract
Workplace type: Remote
Invisible Technologies is an AI training and data collection company that develops high-quality training data to enhance large-scale language models. The company specializes in recruiting domain experts—including general professionals, medical specialists, and language experts—to evaluate and improve AI system performance through structured feedback and testing. Their mission is to make tomorrow's AI smarter, more reliable, and more useful by leveraging human expertise to strengthen model reasoning across diverse fields including healthcare, linguistics, and general knowledge. They work with contractors to provide audio, video, image, and written inputs that support the development and refinement of cutting-edge AI systems.
