Punjabi Music Producer & AI Music Evaluator (Bilingual)

Punjabi Music Producer & AI Music Evaluator (Bilingual)

Full-Time 19350 - 23650 Β£ / year (est.) No working from home possible
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At a Glance

  • Tasks: Evaluate AI-generated music and annotate songs with genre and structure.
  • Company: Join Mercor, a forward-thinking company at the intersection of music and technology.
  • Benefits: Flexible part-time hours and the chance to work with cutting-edge AI.
  • Other info: Immediate start in a creative and innovative environment.
  • Why this job: Shape the future of music while utilising your passion for Punjabi culture.
  • Qualifications: 3+ years in music production and bilingual in Punjabi and English.

The predicted salary is between 19350 - 23650 Β£ per year.

Mercor is hiring experienced musicians to evaluate generative musical AI models in partnership with a leading AI lab. You will assess model outputs across lyrics, voice generation, and other standards, and annotate songs with genre, structure, and vocal/instrumental traits using a structured taxonomy.

Ideal candidates have:

  • 3+ years as music producer/audio engineer
  • A degree in music
  • Native/near-native Punjabi and English proficiency

Immediate start and part-time commitment (10+ hours per week).

Punjabi Music Producer & AI Music Evaluator (Bilingual) employer: Obsidian

At Obsidian, we pride ourselves on fostering a collaborative and innovative work culture that empowers our ML Scientists to push the boundaries of machine learning research. Located in a vibrant tech hub, we offer competitive compensation, flexible project-based work, and ample opportunities for professional growth, making us an excellent employer for those looking to make a meaningful impact in the field of AI.

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Contact Details:

Obsidian Recruitment Team

We think you need these skills to ace Punjabi Music Producer & AI Music Evaluator (Bilingual)

Music Production
Audio Engineering
Generative Music Evaluation
Lyric Assessment
Voice Generation Evaluation
Genre Annotation
Song Structure Analysis