Scientist

Sirius XM • Oakland, CA

1d • Hybrid

About The Position

Design, build, analyze and test machine learning recommender systems or music information retrieval systems for our algorithmic radio and recommendations products. Improve upon existing capabilities of content understanding through analysis of audio data and metadata. Conduct research to discover cutting-edge innovations in the music recognition technology industry. Conduct scientific studies to uncover listener behavior on activity based music stations by observing music consumption. Develop deep-learning-based music audio tagging models. Develop novel techniques for algorithmic radio station generation, leveraging recommender systems and music understanding techniques and data. This role entails hybrid work, with time split between working in our Oakland, CA office and flexibility to telecommute from another U.S. location.

Requirements

• Master’s degree in Computer Science, Statistics, Computational Linguistics, or Music Technology
• 1 year of experience in position offered or as Associate Scientist or Graduate Research Assistant in data science or music technology field.
• All of the required experience must have included designing machine learning systems, recommender systems or music information retrieval system
• programming in Python, Scala, or Java

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level