Machine Learning Engineer

71000 Development · Stockholm, Stockholm
Department 71000 Development
Employment Type Full-time
Minimum Experience Mid-level

About Us

Soundtrack Your Brand is a Spotify-backed company that offers music streaming services for businesses. We serve small customers, like the hairdresser around the corner but also large enterprises like McDonald's, Toni & Guy and TAGHeuer.


Playing music in a business setting is very different from playing music at home. A business music service is pretty much a collaborative, multi-user, multi-location game where businesses need a vast selection of music that's continually updated.


Our product development team consists of 40 very talented, motivated and humble engineers with experiences from places like EA, Spotify, Skype, and Aftonbladet. In total, we are about 80 people working from Sveavägen in Stockholm. We happily support remote working, especially during these times. but we also believe it is important to meet face to face on a regular basis in our Stockholm office.


After building an impressive Nordic customer base early on, the last couple of years, we have expanded internationally and are currently serving tens of thousands of customers across 70 countries, every day.


The Role

The machine learning team at Soundtrack is responsible for many areas of research and application of machine learning including Song Classification, Playlist Continuation, Personalization/Recommendation, User Modeling and Churn Prediction. We work with state of the art in music intelligence research, building services that facilitate world class recommendation and music experience for businesses across the globe.

We work in close collaboration with Product, Music Experts, Analytics and Content teams. We believe that building a successful machine learning feature is about much more than just the ML model. The user experience, overcoming the cold start and the data gathering to continuously improve the features, scalability of the solution, domain coverage, and much more.

We believe that good applications come from good research. We don’t shy away from doing extensive research when we have to. We attend ML conferences and read relevant research as frequently as possible. However, we are mission driven and try to strike a good balance between long and short term goals.

As a member of this team, you will take part in building features that are core to Soundtrack’s value proposition and business. You will work on end-to-end ML solutions: data sourcing, training models, making sure data gathering is in place, and giving feedback on the user experience design. You will report to the Machine Learning Team Lead. 



  • Design, build, evaluate and ship new ML solutions in the areas of responsibility of the team.
  • Collaborate with cross-functional initiatives. Product, Music, Analytics and Content teams will be your most frequent collaborators.
  • Make sure that the right data gathering is in place to continuously improve the ML based features.
  • Build your ideas end-to-end. We believe that the deliverable on ML projects is fully automated training and prediction pipelines combined with satisfying user experience, not just an ML model.
  • Read state of the art research and attend academic conferences to stay on top of the ML literature.
  • Supervise students working on state of the art research.

Preferred experience

  • You have a strong background in machine learning, and good software engineering experience.
  • You have hands-on experience with data engineering tools, able to build and maintain a high-scale pipeline using map-reduce frameworks (spark, dataflow, etc.), able to use orchestration tools (Airflow, Luigi, Argo, Kubeflow Pipelines, etc.) and have good SQL knowledge.
  • Worked with cloud providers (AWS or GCP).
  • Have collaborated with a product team to deliver an ML-based feature in a product.
  • Project management experience is a plus.



  • Always looking to learn more. 
  • A good communicator, able to explain complex machine learning concepts and provide intuition to non-experts.
  • Street smart, crafty, able to build solutions with limited resources.
  • A humble, open person. You say what you mean and mean what you say.
  • Not a perfectionist, but disciplined and methodical in your experimentation and approach to solving problems.
  • Ready to get your hands dirty and join a team of doers!

Thank You

Your application was submitted successfully.

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

  • Location
    Stockholm, Stockholm
  • Department
    71000 Development
  • Employment Type
  • Minimum Experience