Remote Audio Annotation Specialist — Music & Sound Classification

Hire Feed; United Arab Emirates; Remote; AED 90,000 - 120,000; Full time

Job summary

Hire Feed is seeking a Music & Sound Annotation Expert to join on a full-time, remote basis. You will annotate audio data to improve ML models for music and sound classification, leveraging your experience in audio processing and annotation tools.

The role emphasizes accuracy, attention to detail, and the ability to work independently in a global, remote team, with opportunities to contribute to AI-driven audio recognition projects across industries.

Qualifications

• Experience with audio annotation tools such as Audacity, Adobe Audition, or similar software.
• Familiarity with music theory, sound classification, or audio processing.
• Ability to follow detailed instructions and maintain high accuracy.
• Strong attention to detail and ability to work independently in a remote setting.
• Basic understanding of machine learning datasets and their role in AI model training.

Responsibilities

• Annotate and label audio files according to specific guidelines to enhance training datasets.
• Ensure high-quality annotations by following detailed instructions for sound classification tasks.
• Review and validate annotations to maintain consistency and accuracy across datasets.
• Collaborate with the team to refine annotation guidelines and improve data quality.
• Work efficiently to meet deadlines for large-scale audio annotation projects.

Skills

Audio annotation tools

Music theory

Sound classification

Audio processing

Remote work

ML datasets

Tools

Audacity

Adobe Audition

Job description

Hire Feed is seeking a Music & Sound Annotation Expert to join on a full-time, remote basis. You will annotate audio data to improve ML models for music and sound classification, leveraging your experience in audio processing and annotation tools.

The role emphasizes accuracy, attention to detail, and the ability to work independently in a global, remote team, with opportunities to contribute to AI-driven audio recognition projects across industries.