Machine Learning Researcher - Apple Music - Recommender Systems

Summary Posted: Oct 27, 2023 Role Number: 200514847 Join the team that provides personalised recommendations for all Apple Music users. We are behind some of the most loved features in Apple Music, including the Favourites Mix, the Discovery Station, and the Listen Now tab in the app. 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. Our research is application-focused and revolves around machine learning for recommendation: embeddings, tagging, ranking, and sequencing. You will have the opportunity to research cutting edge AI/ML models, 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. We regularly publish research papers at high quality peer-reviewed conferences. You will also be part of Apple’s wider internal 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 Key Qualifications Passion for defining and driving machine learning projects for recommender systems Expertise in modern recommender methods such as neural ranking, RL, counterfactual evaluation and training Solid experience with current Python ML toolkits such as TensorFlow or PyTorch Proven track record of outstanding research publications Excellent communication and presentation skills Experience in Spark SQL is a huge plus Love of music Description 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. Is this you? If so we'd love to hear from you. Education & Experience Education & Experience A PhD/MSc in computer science, statistics, applied mathematics or related field, or equivalent education/experience Additional Requirements Additional Requirements