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OpenTrain AI is looking for an Audio Quality AI Data Reviewer to evaluate audio and robotic video recordings used in artificial intelligence training.
This remote contract opportunity is aimed at people with a professional or academic background in audio engineering, sound production, audio editing or related disciplines. You'll use your listening skills to identify recording problems that automated systems may struggle to recognize reliably.
Compensation ranges from $50 to $90 per hour, with a minimum commitment of 20 hours per week.
What you'll be doing
You'll review audio and robotic video content against established project guidelines, identifying quality issues and documenting your findings accurately.
Your responsibilities will include:
- Reviewing recordings for overall clarity and audio quality.
- Detecting unwanted background noise.
- Identifying clipping and distortion.
- Recognizing echo, hum and other unwanted sounds.
- Detecting audio dropouts and recording inconsistencies.
- Categorizing problems according to predefined guidelines.
- Creating accurate labels and annotations.
- Writing concise notes explaining identified issues.
- Providing clear feedback on reviewed material.
- Applying the same quality standards consistently across large numbers of tasks.
The work is completed independently in a remote environment, so attention to detail and the ability to follow structured instructions are particularly important.
Who they're looking for
You don't necessarily need previous AI training or data annotation experience.
Instead, OpenTrain AI is looking for candidates who already understand audio quality and common recording problems through professional work or academic study.
Relevant backgrounds include:
- Audio engineering.
- Audio production.
- Sound editing.
- Sound production.
- Music technology.
- Audio quality assurance.
- Media review.
- Related audio disciplines.
Experience with audio editing or production software is also valuable.
Skills you'll need
A strong candidate should be able to recognize subtle differences in recording quality and describe those problems clearly.
OpenTrain AI is looking for:
- Strong understanding of audio quality.
- Ability to recognize common recording defects.
- Familiarity with audio editing or production tools.
- Excellent attention to detail.
- Ability to follow structured annotation guidelines.
- Consistent judgment across repetitive evaluation tasks.
- Strong written and verbal English.
- Clear written communication.
Previous experience with data annotation, AI training or media review can help, but isn't required if you already have the relevant audio expertise.
Education & additional experience
A bachelor's degree isn't listed as a strict requirement, but academic training in a relevant field may strengthen your application.
Useful areas of study include:
- Audio Engineering.
- Sound Production.
- Music Technology.
- Audio Production.
- Related technical audio disciplines.
Experience in audio QA, editing, annotation or similar review work may also be advantageous.
Compensation & working hours
The advertised compensation is:
$50–$90 USD per hour
This is a part-time contractor position requiring at least 20 hours per week.
The work is completed remotely.
Location
The opportunity is available across 53 eligible countries, including the United States, Canada, United Kingdom, Netherlands, Spain, France, Germany, Italy, Portugal, Belgium, Switzerland, Austria, Mexico, Brazil, Argentina, Japan, Singapore, India and South Africa, among others.
Candidates should verify that their country is included in the complete eligibility list before applying.
How to apply
The application involves two steps:
- Create a free OpenTrain AI account and submit your resume.
- Continue to the external hiring platform to complete the application process.
About AI audio training
AI systems need large amounts of accurately evaluated data to learn how to interpret real-world audio.
While software can detect some technical problems automatically, experienced listeners can recognize and classify issues such as distortion, clipping, background noise, echo and inconsistent recording quality with greater context and nuance.
As an Audio Quality AI Data Reviewer, you'll apply that expertise to produce structured human feedback that can be used to train and evaluate AI systems.
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