Music Annotation Specialist, Paranaque

We are seeking detail-oriented individuals for the annotation teams to support a large-scale audio preference evaluation and music annotation initiative. The role involves listening to one original audio sample and two synthesized versions, evaluating quality, selecting the best version, and providing structured qualitative feedback. This work will directly contribute to improving next-generation music synthesis and audio AI systems.

• Audio Preference Evaluation:
• Listen to 1 original audio version and 2 synthesized versions of the same content.
• Compare and rate the three samples based on defined criteria such as:
• Audio quality and clarity
• Naturalness and realism
• Musical fidelity
• Artifacts or distortions
• Select the best version among the synthesized outputs.
• Provide clear, concise written remarks explaining the selection.
• Follow standardized evaluation guidelines to ensure consistency across raters.

• Background in musicology, music production, audio engineering, or performance.
• Experience with audio annotation, content labeling, or quality evaluation.
• Familiarity with AI-generated or synthesized audio is a plus.
• Exposure to multiple musical genres and styles.

• Experience in playing instruments (Western), music journalism, audio QA, or related analyst roles.
• Demonstrated ear for musical structure, instrumentation, and production details across multiple genres.
• Comfortable working inside configurable annotation tools, spreadsheets, or content management systems.
• Strong written communication with the ability to summarize subjective listening impressions using precise, grounded language.
• High attention to detail for metadata tagging, file naming, and prompt/model cross-checks.
• Reliable remote setup with headphones suited for repeat listening sessions and the focus to handle long-form writing blocks.

• Background in music theory, ethnomusicology, or audio engineering.
• Experience supporting generative audio, recommender systems, or creator tools.
• Familiarity with data privacy or content sensitivity guidelines for global annotation programs.