At a Glance
- Tasks: Design and build machine learning systems for personalised user experiences at Spotify.
- Company: Join the innovative Personalization team at Spotify, shaping how millions discover music.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative environment with a strong emphasis on creativity and problem-solving.
- Why this job: Make a real impact on user experience while working with cutting-edge technology.
- Qualifications: 5+ years in machine learning, data, or backend engineering with a focus on recommendation systems.
The predicted salary is between 60000 - 80000 € per year.
Requirements
- 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.
What the job involves
- 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.
- 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.
Machine Learning Engineer (Personalization, Samba) employer: Deepstreamtech
As a Machine Learning Engineer at Samba, you will be part of a dynamic team that is dedicated to enhancing user experience through innovative personalization features. Our collaborative work culture fosters creativity and growth, providing ample opportunities for professional development while working on impactful projects that reach millions of users globally. With a focus on cutting-edge technology and a commitment to excellence, we offer a unique environment where your contributions directly influence the future of music and podcast recommendations.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer (Personalization, Samba)
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Spotify or similar companies. Use LinkedIn to connect and engage with them; you never know who might have a lead on your dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those related to recommendation systems. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and problem-solving abilities. Practice coding challenges and be ready to discuss your past experiences with production-grade systems and scalable architectures.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team at StudySmarter.
We think you need these skills to ace Machine Learning Engineer (Personalization, Samba)
Some tips for your application 🫡
Show Off Your Experience:Make sure to highlight your 5+ years of experience in machine learning, data, or backend engineering. We want to see how you've tackled production-grade systems and scalable architectures, so don’t hold back on the details!
Talk About Your Projects:If you've worked on recommendation systems or optimisation problems, share those experiences! We love hearing about real-world applications, so give us the juicy bits about what you did and the impact it had.
Emphasise Collaboration:Since we work across disciplines and geographies, let us know how you've collaborated with different teams. Share examples of how you’ve navigated ambiguity and solved complex problems together—teamwork makes the dream work!
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. Don’t miss out!
How to prepare for a job interview at Deepstreamtech
✨Know Your Stuff
Make sure you brush up on your machine learning concepts, especially around recommendation systems and optimization problems. Be ready to discuss your past experiences in detail, focusing on how you've tackled complex challenges and contributed to production-grade systems.
✨Showcase Your Collaboration Skills
Since the role involves working with cross-functional teams, be prepared to share examples of how you've successfully collaborated with product managers, data scientists, and engineers. Highlight any projects where teamwork led to impactful results, as this will demonstrate your ability to navigate ambiguity and align on goals.
✨Demonstrate User-Centric Thinking
The Personalization team cares deeply about user experience. Think of specific instances where your work has directly improved user satisfaction or engagement. Be ready to discuss how you balance user needs with business outcomes, as this is crucial for the role.
✨Prepare for Technical Questions
Expect to dive into technical discussions during your interview. Brush up on your knowledge of scalable architectures and backend engineering principles. Practise explaining your thought process when designing machine learning systems, as well as how you would approach running experiments to improve performance.
