Apple Music – ML Research Scientist, Recommender Systems

London, Greater London, United Kingdom
Machine Learning and AI

Summary

Posted:
Weekly Hours: 35
Role Number:200335461
The Music ML team helps Apple Music users decide what to play next, whether via the Listen Now tab, or simply by asking Siri. Some of the most loved features in Apple Music are created right here, including the Personal Station and the Chill Mix. Music is our passion, and our aim is to connect artists to music fans like ourselves. Our team members come from 10 countries, creating a diverse, open-minded environment in which we help each other do amazing work — and grow personally. You will have the opportunity to research cutting edge ML models for music recommendation, train the models using massive amounts of data on our GPU grids, and deploy them into our large scale, low-latency services. Supported by world-class engineers. You will also be part of Apple’s wider ML research community, and engage with teams in several locations around the world. The best thing is: here at Apple, innovation never stops. Bring dedication to your job, and you will be part of that innovation that enriches our users lives — the possibilities are boundless.

Key Qualifications

  • proven track record of outstanding publications in recommender systems or personalisation algorithms
  • Solid experience with current Python ML toolkits such as TensorFlow or PyTorch
  • Experience cleaning, manipulating, analysing and modelling data
  • Excellent communication and presentation skills
  • Experience in Spark SQL, Docker is a huge plus
  • Love of music

Description

Apple Music is one of the most exciting recommender system research opportunities not only because of its massive scale, but also because of the wide variety of personalisation products we offer. The Listen Now page with its many personalised rows (from Top Picks to New Releases) is the personal entry page to Apple Music. The personalised mixes and radio stations provide users with carefully sequenced lean-back experiences for chilling, partying or for simply enjoying their all-time favourites. To deliver these experiences, we strongly rely on machine learning, Bayesian modelling and A/B testing. You'll work on some of the most interesting problems in industry-scale recommender systems (from embeddings to counterfactual evaluation), with state of the art resources at Apple, including huge compute grids, top-quality machine learning tools, and massive quantities of data. Based in central London, you will also collaborate with Apple teams in the US and across the world. Is this you? If so we'd love to hear from you. Please include a note with your CV or cover letter to explain your motivation to work for our team.

Education & Experience

A PhD in computer science, statistics, applied mathematics or related field, or equivalent education/experience

Additional Requirements