Machine Learning Researcher - Apple Music - Recommender Systems

Lex; Greater London; On-site; GBP 95,000 - 130,000; Full time

Job summary

Apple Music's ML research team in London is seeking a senior researcher to advance recommender systems powering features across the service. You will research, train and deploy state-of-the-art AI/ML models at scale, on huge datasets, while upholding privacy and performance requirements.

You will collaborate with leading researchers and engineers, run experiments, publish findings, and translate insights into product decisions that improve discovery and personalization for listeners and artists

Qualifications

• Experience leading recommender-system projects from research through to production at scale.
• Peer-reviewed publications at top venues (e.g., RecSys, SIGIR, KDD, NeurIPS).
• Expertise in modern recommender methods (neural ranking, RL, sequential, generative).
• Proficient with Python ML toolkits such as TensorFlow or PyTorch.
• Excellent communication and presentation skills.

Responsibilities

• Research AI/ML models for recommendation and broader personalization.
• Train and fine-tune models on large GPU grids and data.
• Deploy models into large-scale, low-latency services.
• Run experiments and translate results into product decisions.
• Collaborate with researchers and engineers across Apple ML teams.

Skills

ML recommender systems

Publications in top venues

Modern recommender methods

Python ML toolkits (TensorFlow, PyTorh

Communication skills

Education

PhD/MSc in CS/Statistics/Math or related field

Tools

TensorFlow

PyTorch

Job description

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 Playground.

Music 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 found.

Our team members come from 10 countries, creating a diverse, open-minded environment in which we help each other do amazing work and grow.

Here 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.

Description

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 experience.

You 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 find.

You will work alongside some of the best researchers and engineers in the field, connected to Apple's wider internal ML research community. We hire great people and trust them to do their best work. It's the people who make it exciting to work here every day, and you will be one of them.

Is this you? If so, we'd love to hear from you.

Minimum Qualifications

• Track record of leading ML recommender system projects from research through to production at scale
• Peer-reviewed publications at venues such as RecSys, SIGIR, KDD, ISMIR, NeurIPS, ICLR, ICML or related
• Expertise in modern recommender methods (e.g. multi-interest, neural ranking, RL, sequential, generative)
• Solid experience with Python ML toolkits such as TensorFlow or PyTorch
• Excellent communication and presentation skills
• A PhD/MSc in computer science, statistics, applied mathematics or related field, or equivalent education/experience

Preferred Qualifications

• Familiarity with LLM methods applied to recommendation
• Experience with counterfactual evaluation
• Experience with Spark SQL
• Love of music

At Apple, we're not all the same. And that's our greatest strength. We draw on the differences in who we are, what we've experienced and how we think. Because to create products that serve everyone, we believe in including everyone. Therefore, we are committed to treating all applicants fairly and equally. As a registered Disability Confident employer, we will work with applicants to make any reasonable accommodations. Apple will consider for employment all qualified applicants with criminal backgrounds in a manner consistent with applicable law. Learn more

At Apple, we believe accessibility is a fundamental human right. You'll find that idea reflected in everything here - in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.

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Role Number: 200665642-2114