Professional Musician - Audio Annotation Project (Music Instrument & Stem Identification)

About Turing:

Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L.

Role Overview:

We are looking for experienced global talent with a formal music degree/field of study and music-related performance, production, and audio engineering to support an AI annotation project focused on evaluating, reviewing, and improving content generated by AI systems.

The client's research team is building training data to extend music source separation models beyond today's standard 4–6 stems. Annotators will listen to short audio clips and identify the instruments present, helping create a fine-grained dataset for next-generation audio separation research.

Key Responsibilities:

• Listen to three 5-second audio segments drawn from different positions in the same track Identify the instrument family (e.g. Brass, Strings, Woodwind, Percussion, Keyboard) and the specific instrument playing.
• Identify the instrument family and the specific instrument in given tracks. Use reference examples grouped by family, shown alongside each task, to guide your answer.
• Follow detailed annotation guidelines and maintain high consistency and quality standards.
• Contribute to guidelines, reference materials, and quality improvement initiatives where required.

Required Skills and Qualifications:

• Bachelor's degree in Music or related field.
• 3 years of experience in music-related performance, production, and audio engineering.
• Strong command of written and spoken English.
• Strong, trained ear for identifying instruments and instrument families by sound.
• Comfortable working independently against short, repetitive listening tasks (~1 minute per task).
• Experience with remixing, transcription, music information retrieval and AI/data annotation projects is an advantage.
• Reliable internet access and ability to work on the GALA annotation platform.

Perks of Freelancing with Turing:

• Work on the cutting edge of AI.
• Fully remote and flexible work environment.
• Exposure to advanced LLMs and insight into how they’re trained.

Offer Details:

• Commitments Required: Pay Per Task.
• Employment type : Contractor assignment (no medical/paid leave).
• Duration of contract  2 days.

Evaluation Process:

• Interested candidates must complete an assessment to complete their application.
• Shortlisting will be based on qualifications and relevant professional experience.