Air Traffic Control Audio Transcription Expert

You will turn authentic air traffic control radio transmissions into accurate, structured transcripts for aviation communications AI training. You will use operational context to clarify difficult audio and meet a target word error rate of 2% or lower.

• Transcribe air traffic control radio communications accurately.
• Identify headings, altitudes, frequencies, clearances, and other critical instructions.
• Use airport diagrams, approach charts, and aircraft-position information to improve transcription accuracy.
• Resolve unclear or noisy audio using air traffic control experience and aviation context.
• Review feedback and improve transcript quality over time.
• Protect confidential data and follow project security protocols.

What it pays and takes

This is a remote, part-time contractor opportunity for an individual air traffic control professional. The role is marked as entry level, with specialist certification and aviation communication skills required.

• Pay: $30 to $50 per hour.
• Work arrangement: Remote contractor work.
• Location: Open to candidates in the listed countries.
• Language: Fluent written and verbal English with strong aviation phraseology.
• Required: Current or previous certification as an air traffic controller in tower, approach, center, or ground operations.
• Required: Ability to understand a wide range of accents, including international pilot communications.
• Required: Strong attention to detail and consistency against demanding accuracy targets.
• Required: Ability to work independently with structured guidelines.
• Helpful: Experience with aviation maps, approach charts, navigation tools, and aircraft-position information.
• You need reliable internet, a distraction-free workspace, and quality headphones for critical listening.

How it works

You apply on OpenTrain with your resume and then complete the application on the hiring site.

About AI training work

AI training work uses examples prepared and reviewed by people to help artificial intelligence systems learn. Audio transcription contributors turn real speech into accurate training data, and people with relevant professional experience can help capture details that general transcription may miss.