Machine Learning Engineer
Confirmed on the employer's own hiring board on Oct 21, 2026. First seen by Alion on Oct 20, 2026. Apple scores A on the Alion truth index.
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 at Apple Media Products is responsible for personalisation and recommendation in Apple Music. We are looking for an experienced Software 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 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 dynamic data systems. We are responsible for the full lifecycle: collaboration with the Product team, system design, implementation, continuous optimisation and improvement.
Minimum Qualifications
Hands-on experience crafting highly scalable recommendations systems
Understanding of concurrency, algorithms and object oriented programming
A vision of how to engineer modern ML-driven systems that allow for fast iteration cycles
Effective collaboration with researchers to improve recommendation algorithms
Preferred Qualifications
A vision of how to engineer modern ML-driven pipelines, APIs and services at scale
Extensive experience with object-oriented languages such as Java, C++, and Python