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Strong Tier-1 brand and metro location increase competition, though specialized ML role narrows the candidate pool.
Highly specialized ML/NLP/CV requirements limit transferability across non-ML industries.
Specialized ML/NLP/CV skills, production model deployment experience, and research expectations imply strict technical screening.
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Design and develop end-to-end systems to improve music catalog metadata quality using AI and machine learning techniques.
Collaborate cross-functionally with scientists, engineers, and product managers to frame and solve complex business problems with ML solutions.
Analyze large datasets to create scalable models, deploy them into production, and provide actionable insights for continuous catalog improvement.
Bachelor's degree or higher in Engineering, Computer Science, Machine Learning, Operations Research, Statistics, or a related field.
Experience programming in Java, C++, Python, or related languages.
Experience building machine learning models or developing algorithms for business applications.
Experience with design of experiments and statistical analysis of results.
Proven ability to lead technical projects from research to production deployment within a cross-functional team environment.
Strong background in machine learning, deep learning, NLP, or computer vision research, preferably with publications in peer-reviewed venues.
Comfortable working on scalable AI solutions involving large datasets and complex business integration.