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