At a Glance
- Tasks: Research and develop cutting-edge AI/ML models for music recommendations.
- Company: Join Apple Music, a leader in connecting artists with fans.
- Benefits: Competitive salary, diverse culture, and opportunities for growth.
- Other info: Collaborate with top researchers in a dynamic, innovative environment.
- Why this job: Make a real impact on how millions discover their next favourite song.
- Qualifications: Experience in ML recommender systems and strong Python skills.
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 employer: Apple
At Apple Music, we foster a vibrant and inclusive work culture where innovation thrives and every team member's contribution is valued. As a Machine Learning Researcher, you'll collaborate with top-tier talent in a diverse environment, working on cutting-edge AI/ML projects that enhance the music experience for millions. With a commitment to employee growth and well-being, we offer unique benefits and opportunities that empower you to excel in your career while pursuing your passion for music.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Researcher - Apple Music - Recommender Systems
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those working at Apple Music or similar companies. A friendly chat can lead to insider info about job openings and even referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML projects, especially those related to recommender systems. Share it on platforms like GitHub and make sure it's easy for recruiters to see what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your communication skills. Practice explaining complex ML concepts in simple terms, as you'll need to convey your ideas clearly to both technical and non-technical folks.
✨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 our careers page for any new opportunities that pop up!
We think you need these skills to ace Machine Learning Researcher - Apple Music - Recommender Systems
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 in leading ML recommender system projects. Talk about your peer-reviewed publications and any specific techniques you've used. We’re looking for solid evidence of your expertise, so don’t hold back on the details!
Tailor Your Application:Customise your application to fit the job description. Use keywords from the posting, like 'neural ranking' or 'counterfactual evaluation', to demonstrate that you understand what we’re looking for. This shows us that you’ve done your homework and are genuinely interested in the position.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it makes the process smoother for both you and us. So, don’t hesitate—get your application in today!
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 peer-reviewed publications and how they relate to the role.
✨Show Your Passion for Music
Since this role is all about connecting artists with fans, let your love for music shine through. Share your favourite artists or playlists and how they inspire your work in machine learning. This personal touch can make a big difference!
✨Prepare for Technical Questions
Expect to dive deep into technical discussions about Python ML toolkits like TensorFlow or PyTorch. Brush up on modern recommender methods and be prepared to explain complex concepts clearly. Practice explaining your thought process as if you're teaching someone else.
✨Communicate Clearly
Excellent communication skills are key. Practice presenting your ideas and findings succinctly. Use examples from your experience to illustrate your points, and don’t hesitate to ask clarifying questions if you need more information during the interview.
