Image Annotation Support Drone Operations

Role: Image Annotation Support - Drone Operations
Duration: 5 Months (Contract)
Location: Nashville TN (On-Site)

Key Skills: Image Annotatio; Image Labeling; Visual Observation (Drone Visual Observer) Airport Pavement Inspection

Seeking a contract worker to support airport pavement data drone operations and general office tasks.
The main duty of this position will be tracing pavement cracks from airfield pavement images. This work will help the Division develop a machine-learning tool to better identify pavement cracks and support future pavement maintenance decisions.

Primary Duties

• Review pavement images and trace visible cracks.
• Label crack data using Division guidance.
• Help organize completed image files and tracking logs.
• Identify unclear images or issues for staff review.
• Support quality control of crack-tracing work.

• Serve as a visual observer during drone flights.
• Watch the drone surrounding airspace people vehicles and airport activity.
• Communicate with the drone pilot and field staff during flights.
• Help with basic field notes photos and data organization.
• File scan rename and organize project documents.
• Assist with spreadsheet updates and data entry.
• Perform other related support tasks as assigned.

• High school diploma or equivalent.
• Basic computer skills.
• Strong attention to detail.
• Ability to follow instructions.
• Ability to work independently after training.
• Ability to work in an office setting and occasionally in the field.
• Valid drivers license preferred.

• Experience with Excel SharePoint OneDrive Teams or similar tools.
• Interest or experience in drones aviation pavement GIS CAD construction or data entry.
• Ability to stay organized and complete repetitive tasks accurately.

Work Environment
Most work will be computer-based. Some work may occur at airports and may include walking standing heat sun wind aircraft activity and active pavement areas.
Purpose
This position supports airport pavement program by helping create accurate data for a machine-learning tool that can improve pavement inspections maintenance planning and long-term asset management.


Email resumes to to apply!