Machine Learning Engineer

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 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.

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

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.

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 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.