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Machine Learning Researcher Apple Music Recommender Systems
Job Location:
Job Location:
London, KY - USA
Monthly Salary:
Not provided by the employer
Monthly Salary:
Posted:
13 July 2026 (30+ days ago)
Posted:
Application Deadline:
10 October 2026
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
Join the team that helps all Apple Music users discover music they will love. We are behind some of the most popular features in Apple Music including the Home and New tabs Discovery Station and Playlist is our passion and our aim is to connect artists with music fans. Two people are always on our minds: the listener trying to find their next favourite and the artist trying to be team members come from 10 countries creating a diverse open-minded environment in which we help each other do amazing work and at Apple innovation never stops. Bring dedication to your job and you will be part of the innovation that enriches our users lives. The possibilities are boundless.n
Your work at Apple Music will become part of a product that deeply cares for music and for the privacy of our users in a way no other company can match. We work at massive scale and across a wide variety of personalisation products that touch every aspect of the Apple Music will research AI/ML models for recommendation bespoke and foundational that push the state of the art. You will train and fine-tune them on huge GPU grids and massive quantities of data and help deploy them into our large-scale low-latency services. You will run experiments translate results into product decisions and publish what you will work alongside some of the best researchers and engineers in the field connected to Apples wider internal ML research community. We hire great people and trust them to do their best work. Its the people who make it exciting to work here every day and you will be one of this you If so wed love to hear from
Track record of leading ML recommender system projects from research through to production at scalenPeer-reviewed publications at venues such as RecSys SIGIR KDD ISMIR NeurIPS ICLR ICML or relatednExpertise in modern recommender methods (e.g. multi-interest neural ranking RL sequential generative)nSolid experience with Python ML toolkits such as TensorFlow or PyTorchnExcellent communication and presentation skillsnA PhD/MSc in computer science statistics applied mathematics or related field or equivalent education/experience
Familiarity with LLM methods applied to recommendationnExperience with counterfactual evaluationnExperience with Spark SQLnLove of musicn
Your work at Apple Music will become part of a product that deeply cares for music and for the privacy of our users in a way no other company can match. We work at massive scale and across a wide variety of personalisation products that touch every aspect of the Apple Music will research AI/ML models for recommendation bespoke and foundational that push the state of the art. You will train and fine-tune them on huge GPU grids and massive quantities of data and help deploy them into our large-scale low-latency services. You will run experiments translate results into product decisions and publish what you will work alongside some of the best researchers and engineers in the field connected to Apples wider internal ML research community. We hire great people and trust them to do their best work. Its the people who make it exciting to work here every day and you will be one of this you If so wed love to hear from
Track record of leading ML recommender system projects from research through to production at scalenPeer-reviewed publications at venues such as RecSys SIGIR KDD ISMIR NeurIPS ICLR ICML or relatednExpertise in modern recommender methods (e.g. multi-interest neural ranking RL sequential generative)nSolid experience with Python ML toolkits such as TensorFlow or PyTorchnExcellent communication and presentation skillsnA PhD/MSc in computer science statistics applied mathematics or related field or equivalent education/experience
Familiarity with LLM methods applied to recommendationnExperience with counterfactual evaluationnExperience with Spark SQLnLove of musicn
Required Experience:
IC
About Company
Ask Siri to name the most successful company in the world and it might respond: Apple. And it's not just out of familial pride. Apple consistently ranks highly in profit, revenue, market capitalization, and consumer cachet. In 2018, the company became the first reach a trillion dollar ... View more
