At a Glance
- Tasks: Design and build machine learning systems for personalised music recommendations.
- Company: Join Spotify's innovative Personalization team, shaping the future of music discovery.
- Benefits: Flexible work options, extensive learning opportunities, and generous parental leave.
- Other info: Inclusive culture that values diverse perspectives and supports your personal growth.
- Why this job: Make a real impact on millions of users' listening experiences with cutting-edge technology.
- Qualifications: 5+ years in machine learning or backend engineering, with experience in recommendation systems.
The predicted salary is between 70000 - 90000 € per year.
The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Blend to Discover Weekly, we’re behind some of Spotify’s most-loved features. We built them by understanding the world of music and podcasts better than anyone else. Join us and you’ll keep millions of users listening by making great recommendations to each and every one of them. Samba sits at the heart of Spotify’s personalization engine, powering experiences like autoplay, radio, and personalized mixes. We work on complex sequencing and optimization problems—balancing what users love with how Spotify supports creators and the business. Our team blends machine learning, backend engineering, and data expertise, and collaborates across North America and Europe to deliver impactful, real-time personalization at scale.
What You’ll Do
- Design and build machine learning systems that optimize ranking and sequencing across personalized surfaces
- Develop multi-objective optimization strategies that balance user satisfaction with business outcomes
- Collaborate closely with cross-functional partners including product, data science, and engineering teams to align on goals, share context, and deliver impactful solutions
- Work across ML, backend, and data layers to bring models into production
- Contribute to scalable infrastructure supporting high-volume user interactions
- Run experiments and use insights to continuously improve performance
- Help shape technical direction and raise the bar for engineering excellence within the team
Who You Are
- You have 5+ years of experience in machine learning, data, or backend engineering
- You are experienced with production-grade systems and scalable architectures
- You have worked on recommendation systems, ranking, or optimization problems
- You bring a T-shaped skillset across ML, data, and backend domains
- You are comfortable navigating ambiguity and solving complex problems
- You care about user experience and measurable impact
- You enjoy collaborating across disciplines and geographies
Where You’ll Be
This role is based in London or Stockholm. We offer you the flexibility to work where you work best! There will be some in-person meetings, but still allows for flexibility to work from home.
Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens. At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we’re here to support you in any way we can.
Extensive learning opportunities, through our dedicated team, GreenHouse. Flexible share incentives letting you choose how you share in our success. Global parental leave, six months off - for all new parents. All The Feels, our employee assistance program and self-care hub. Flexible public holidays, swap days off according to your values and beliefs.
Machine Learning Engineer, Personalization employer: Spotify AB
Spotify is an exceptional employer that fosters a culture of inclusivity and collaboration, making it a fantastic place for Machine Learning Engineers to thrive. With extensive learning opportunities, flexible work arrangements, and a commitment to employee well-being, Spotify empowers its team members to innovate and make a meaningful impact on millions of users worldwide. The vibrant locations of London and Stockholm offer a dynamic environment where creativity and technology intersect, ensuring that every employee can contribute to the future of music and podcasts.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer, Personalization
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Spotify. A friendly chat can open doors that applications alone can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those related to recommendation systems. This will give us a taste of what you can bring to the table.
✨Tip Number 3
Prepare for the interview by brushing up on your knowledge of ML, backend engineering, and data expertise. We love candidates who can discuss complex problems and their solutions confidently.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're serious about joining our team!
We think you need these skills to ace Machine Learning Engineer, Personalization
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Machine Learning Engineer role. Highlight your work on recommendation systems and any relevant projects that showcase your expertise in ML, data, and backend engineering.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about personalisation and how your background makes you a great fit for our team. Share specific examples of how you've tackled complex problems and collaborated across disciplines.
Showcase Your Projects:If you've worked on any machine learning projects, especially those involving ranking or optimisation, make sure to include them in your application. We love seeing real-world applications of your skills!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Spotify AB
✨Know Your Machine Learning Stuff
Make sure you brush up on your machine learning concepts, especially around recommendation systems and optimization problems. Be ready to discuss your past projects and how they relate to the role at Spotify.
✨Show Off Your Collaboration Skills
Spotify values teamwork, so be prepared to share examples of how you've worked with cross-functional teams in the past. Highlight any experiences where you aligned goals with product or data science teams to deliver impactful solutions.
✨Prepare for Technical Questions
Expect some technical questions that dive deep into your experience with production-grade systems and scalable architectures. Practise explaining complex concepts clearly and concisely, as if you're teaching someone new to the field.
✨Emphasise User Experience
Since this role is all about enhancing user experience, come equipped with ideas on how to balance user satisfaction with business outcomes. Share insights from your previous work that demonstrate your understanding of user needs and measurable impact.
