Role Number: 200627345-0399

Responsibilities

• Analyze and evaluate music datasets for musical characteristics and high quality across genres.
• Analyze musical characteristics of large-scale datasets using Python.
• Create and curate music datasets through recording sessions, synthetic data generation, and musical content creation.
• Collaborate with data engineers to develop data curation strategies that ensure musical authenticity and diversity.
• Validate model outputs and training results for musical correctness, coherence, and creative quality.
• Document musical characteristics, metadata requirements, and quality standards for music datasets.
• Design evaluation criteria and test cases that assess ML models from a musical perspective.
• Work with ML researchers and engineers to communicate musical requirements and provide domain expertise.

Minimum Qualifications

• Bachelor’s degree (or higher) in Audio Production, Musicology, Music Technology, or related field, or 3 years of equivalent professional work experience
• Experience with Python programming and data analysis using pandas or similar libraries
• Understanding of machine learning concepts and audio signal processing fundamentals
• Advanced knowledge of music theory, harmony, composition, and instrumentation across multiple genres

Preferred Qualifications

• Familiarity with music analysis libraries such as librosa or music21
• Experience analyzing large music datasets or music information retrieval research
• Experience curating large-scale, multi-language music datasets for LLM fine-tuning and model adaptation workflows
• Expert in music creation tools such Logic Pro
• Experience working on music research or data-driven music projects
• Experience with data visualization for music analysis or dataset exploration
• Knowledge of ML model evaluation methodologies and quality metrics
• Strong attention to detail and commitment to data accuracy and quality
• Fluent in English