Senior Machine Learning Engineer - Music Recommendation Engine

Senior Machine Learning Engineer - Music Recommendation Engine

Full-Time 68205 - 80000 £ / year (est.) No working from home possible
Apple

At a Glance

  • Tasks: Build and improve music recommendation features for millions of users.
  • Company: Join Apple, a leader in innovation and technology.
  • Benefits: Competitive salary, flexible work options, and opportunities for growth.
  • Other info: Collaborative team culture with diverse backgrounds and global reach.
  • Why this job: Make a real impact on how people discover music they love.
  • Qualifications: Experience in machine learning and large-scale systems required.

The predicted salary is between 68205 - 80000 £ per year.

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.

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.

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 personalised 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

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.

Senior Machine Learning Engineer - Music Recommendation Engine employer: Apple

At Apple, we foster a culture of innovation and collaboration, where your passion for music and technology can thrive. As part of our London-based Music ML team, you'll have the opportunity to work on cutting-edge machine learning systems that enhance the Apple Music experience for millions globally. With a commitment to employee growth, a diverse team, and a focus on privacy, Apple is an exceptional employer for those looking to make a meaningful impact in the tech industry.

Apple

Contact Details:

Apple Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior Machine Learning Engineer - Music Recommendation Engine

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We think you need these skills to ace Senior Machine Learning Engineer - Music Recommendation Engine

Machine Learning
Software Engineering
Data Analysis
Distributed Systems
Personalisation Algorithms
A/B Testing
Feature Engineering

Some tips for your application 🫡

Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.

Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Apple.

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Apple and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!

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How to prepare for a job interview at Apple

Brush Up on Your Coding Skills

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Prepare for Behavioural Questions

While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.