Music Data Engineer
vor 4 Wochen
Role Number: 200627345-0399 Responsibilities Analyze and evaluate music datasets for musical characteristics and high quality across genres.Bewerben Sie sich umgehend Für die unten beschriebene Stelle wird eine hohe Anzahl von Bewerbern erwartet, warten Sie also nicht mit der Einsendung Ihres Lebenslaufs.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
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