Senior Machine Learning Engineer – Search

  • Full Time
  • London, UK
  • Applications have closed
  • 6

Spotify is looking for Machine Learning Engineers to join our team. You will work on a variety of problems such as personalization, targeting, optimization and similar. Being a part of a team, you will come up with new and interesting hypotheses, test them, and scale them up to massive data sets, so that your algorithms and models can be used to improve critical components in the Spotify products. Above all, your work will impact the way our 200 million users experience music.

This is a generic advert describing the baseline of skills and experiences that we are looking for, but we are recruiting to multiple teams. Our process is open-ended in the sense that we will route you to different teams based on the findings in the recruitment process and your area of interest for the best match.

Right now, we will not be considering new graduates for these roles. 

What you’ll do

  • Work on business critical problems by applying machine learning to massive data sets

  • Prototype new algorithms, evaluate with small scale experiments, and later productionize solutions at scale to our >200 million active users

  • Work with agile teams of software/data engineers, machine learning engineers, designers, product managers and others to build new product features

  • Help drive optimization, testing and tooling to improve data quality

  • Iterate on quality of machine learning powered features through continuous A/B testing

  • Work from our office in London

Who you are

  • Ph.D. or M.Sc. in Machine Learning, or related field (e.g. applied mathematics/statistics) and work experience from industry in this field

  • You have a strong mathematical background in statistics and machine learning

  • You have experience of feature engineering and prototyping machine learning applications, that have been deployed to production

  • You are well-versed in programming and scripting (not only R and Matlab)

  • You preferably have machine learning publications or open source contributions to share with us

  • Bonus: experience with data processing and storage frameworks like Hadoop, Scalding, Spark, Storm, Google Dataflow, etc.

  • Bonus: experience implementing machine learning systems at scale in Java, Scala, TensorFlow or similar

We are proud to foster a workplace free from discrimination. We truly believe that diversity of experience, perspectives, and background will lead to a better environment for our employees and a better product for our users and our creators. This is something we value deeply and we encourage everyone to come be a part of changing the way the world listens to music.