At a Glance
- Tasks: Research and develop cutting-edge AI/ML models for music recommendations at Apple Music.
- Company: Join the innovative team at Apple Music, passionate about connecting artists and fans.
- Benefits: Competitive salary, diverse culture, and opportunities for personal and professional growth.
- Other info: Collaborate with top researchers in a dynamic, inclusive environment.
- Why this job: Make a real impact on how millions discover their next favourite songs.
- Qualifications: Experience in ML recommender systems and strong Python skills required.
The predicted salary is between 60000 - 80000 £ per year.
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. 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.
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.
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.
Machine Learning Researcher - Apple Music - Recommender Systems in London employer: Apple
At Apple Music, we pride ourselves on fostering a vibrant and inclusive work culture where innovation thrives. As a Machine Learning Researcher, you'll collaborate with a diverse team of experts, pushing the boundaries of music recommendation technology while enjoying ample opportunities for professional growth. With a commitment to employee well-being and a passion for music, Apple Music offers a unique environment that empowers you to make a meaningful impact in the lives of music lovers worldwide.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Researcher - Apple Music - Recommender Systems in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those working at Apple Music or similar companies. Use LinkedIn to connect and don’t be shy about asking for informational interviews – it’s a great way to learn and get your name out there.
✨Tip Number 2
Show off your passion for music and machine learning! When you get the chance to chat with recruiters or during interviews, share your favourite projects or research. Let them see how your love for music aligns with their mission at Apple Music.
✨Tip Number 3
Prepare for technical interviews by brushing up on your ML knowledge. Practice explaining your past projects clearly and concisely, focusing on your contributions and the impact they had. Remember, they want to see how you think and solve problems!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, keep an eye on any upcoming events or webinars hosted by Apple – they’re a fantastic opportunity to learn more and make connections.
We think you need these skills to ace Machine Learning Researcher - Apple Music - Recommender Systems in London
Some tips for your application 🫡
Show Your Passion for Music:When you're writing your application, let your love for music shine through! Mention how your passion connects with the role and how it drives your work in machine learning. We want to see that you’re not just a tech whiz but also someone who truly cares about enhancing the music experience.
Highlight Relevant Experience:Make sure to showcase your track record with ML recommender systems. Talk about specific projects you've led from research to production. We’re looking for solid examples that demonstrate your expertise and how you can contribute to our team at Apple Music.
Be Clear and Concise:Keep your application clear and to the point. Use straightforward language to explain your skills and experiences. We appreciate well-structured applications that make it easy for us to see why you’d be a great fit for the role!
Apply Through Our Website:Don’t forget to apply through our official website! It’s the best way for us to receive your application and ensure it gets the attention it deserves. Plus, it shows you’re serious about joining our amazing team at Apple Music.
How to prepare for a job interview at Apple
✨Know Your Stuff
Make sure you brush up on the latest trends in machine learning and recommender systems. Be ready to discuss your past projects, especially those that led to production at scale. Highlight your experience with Python ML toolkits like TensorFlow or PyTorch, as these are crucial for the role.
✨Show Your Passion for Music
Since this role is all about connecting music lovers with their next favourite track, let your passion for music shine through. Share your thoughts on how music influences recommendations and any personal projects related to music that you've worked on.
✨Prepare for Technical Questions
Expect to dive deep into technical discussions during your interview. Brush up on modern recommender methods and be prepared to explain concepts like multi-interest models, neural ranking, and reinforcement learning. Practising coding problems related to these topics can also give you an edge.
✨Communicate Clearly
Excellent communication skills are a must for this role. Practice explaining complex ideas in simple terms, as you'll need to translate your research findings into actionable product decisions. Consider doing mock interviews to refine your presentation skills and get comfortable discussing your work.
