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Senior Machine Learning Engineer - Music Recommendation Engine

Apple· London, England, United Kingdom
Posted 10 Jun 2026Machine Learning Engineer
Apple4.1 (14,142)10,000+ employeesnomatch
Levels.fyi · global compEM $468k TC ($468k–$468k)SWE $318k TC ($220k–$403k)
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Summary

Here at Apple new ideas have a way of becoming great products very quickly, and innovation never stops. Bring passion and dedication to your job and there's no telling what you could accomplish.

The Music ML team within Apple Services Engineering is responsible for personalisation and recommendation in Apple Music. We are looking for an experienced Software or Machine Learning Engineer to help design and run our customer-facing recommendation services reliably, efficiently, and with dedication to delivering relevant and diverse music to our users.

Music is our passion, and our aim is to connect artists to music lovers like ourselves. We build amazing experiences for our users while respecting their privacy. Our team is a friendly bunch of people from more than 10 countries. We help each other grow and realise the best work for our users.

We’re also part of a larger team at Apple Services Engineering and beyond. We work together to realise a single unified vision, making use of Apple’s unique integration of hardware, software, and services. And although services are a bigger part of Apple’s business than ever before, these teams remain small, nimble, and cross-functional, offering great opportunities to collaborate and grow.

Description

The Music ML team within Apple Services Engineering is looking for a great Software or Machine Learning Engineer to build and improve the features and services driving Apple Music personalisation.

Our team is responsible for providing personalised features for Apple Music including Home, New, Radio, and Personal Mixes. Our work includes data analysis, large-scale offline pipelines, machine-learned model training and inference, and online services to provide real-time personalised experiences. Our growing London-based team builds and evolves global-scale, leading-edge machine learning systems and distributed systems that serve recommendations to users around the world.

We are responsible for the full lifecycle: collaboration with the Product team, system design, implementation, continuous optimisation and improvement.

If this sounds exciting to you, we’d love to hear from you. Adding a cover letter to explain your passion for this particular job is greatly appreciated.

Responsibilities

Building products and services for millions of users with a focus on great customer experience and privacy

Developing complex systems that integrate data from many sources to deliver on-the-fly personalisation with low latency

Tuning performance considering both latency and throughput

Deploying our systems globally for improved resiliency and end-user experience

Collaborating across teams to take new user-facing features from conception to production

Working within our team to develop and deploy massive datasets to improve personsalised features

Prototyping algorithm changes and launching A/B tests to measure changes to personalised products

Minimum Qualifications

Hands-on experience engineering and maintaining large distributed backend systems

Hands-on experience with applied machine learning systems at production scale

Understanding of concurrency, algorithms and object oriented programming

Effective collaboration with researchers to improve machine learning models

Preferred Qualifications

A vision of how to engineer modern ML-driven pipelines, APIs and services at scale, with fast iteration cycles

Ability to own and lead projects from conception through to design and implementation

Experience with recommender systems, feature engineering

Experience designing and running customer-facing A/B tests

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.

Learn about accessibility in Apple’s workplace

Role Number: 200656273-2114