At a Glance
- Tasks: Build and enhance features for Apple Music personalisation using cutting-edge technology.
- Company: Join the innovative team at Apple, where creativity thrives.
- Benefits: Competitive salary, health benefits, and opportunities for professional growth.
- Why this job: Make a real impact on millions of users with your passion for music and technology.
- Qualifications: Experience in scalable recommendation systems and strong programming skills.
- Other info: Dynamic work environment with a commitment to diversity and inclusion.
The predicted salary is between 36000 - 60000 ÂŁ 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 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 personalised 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.
Minimum Qualifications
- Hands‑on experience crafting highly scalable recommendation 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
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.
Senior Software/Machine Learning Engineer - Apple Music employer: Apple
Contact Detail:
Apple Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Software/Machine Learning Engineer - Apple Music
✨Tip Number 1
Network like a pro! Reach out to current or former employees at Apple Music on LinkedIn. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Show off your skills! If you’ve got a portfolio or GitHub with projects related to machine learning or software engineering, make sure to highlight that in conversations. It’s a great way to demonstrate your expertise.
✨Tip Number 3
Prepare for the interview by brushing up on your technical skills. Expect to tackle coding challenges and system design questions. Practising these will help you feel more confident and ready to impress.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in being part of the Apple Music team.
We think you need these skills to ace Senior Software/Machine Learning Engineer - Apple Music
Some tips for your application 🫡
Show Your Passion: When writing your application, let your enthusiasm for the role shine through! We want to see why you're excited about working on Apple Music and how you can contribute to our mission of personalisation.
Tailor Your CV: Make sure your CV is tailored to highlight your experience with scalable recommendation systems and machine learning. We love seeing how your skills align with what we do, so don’t hold back!
Craft a Compelling Cover Letter: A cover letter is your chance to tell us your story. Explain why this role at Apple Music excites you and how your background makes you a perfect fit. We appreciate a personal touch!
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can’t wait to hear from you!
How to prepare for a job interview at Apple
✨Know Your Stuff
Make sure you brush up on your knowledge of machine learning algorithms and recommendation systems. Be ready to discuss your hands-on experience with scalable systems, as well as any projects you've worked on that relate to personalisation in music or similar fields.
✨Show Your Passion
Apple loves candidates who are genuinely excited about their work. Prepare a cover letter that highlights your passion for music and technology, and be ready to share why you want to be part of the Apple Music team specifically. This will help you stand out!
✨Collaboration is Key
Since the role involves working closely with product teams and researchers, think of examples where you've successfully collaborated across teams. Be prepared to discuss how you approach teamwork and communication, especially in complex projects.
✨Think Performance
Understand the importance of performance tuning in your systems. Be ready to talk about how you’ve optimised latency and throughput in past projects. This shows that you not only know how to build systems but also how to make them efficient and user-friendly.