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Spotify is looking for an exceptional Machine Learning Engineer to join our team. You will work on a variety of problems such as content recommendation, personalization, optimization, user intelligence, and content classification. You will work with a team to come up with new and interesting hypotheses, test them, and scale them up to huge data sets with hundreds of billions of data points. Above all, your work will impact the way the world experiences music.
Currently we are only looking for senior people for this position, i.e. people with experience from applied machine learning in production systems, preferably at large scale, as well as a strong engineering background.
What you'll do
Apply machine learning, collaborative filtering, NLP, and deep learning methods to massive data sets
Prototype new algorithms, evaluate with small scale experiments, and later productionize solutions at scale to our >100 million active users
Collaborate with a cross-functional agile team of software engineers, data engineers, ML experts, and others to build new product features
Help drive optimization, testing and tooling to improve data quality
Iterate on recommendation quality through continuous A/B testing
Work from our office in Stockholm.
Who you are
Ph.D. or M.Sc. in Machine Learning, or related field
You have experience implementing machine learning systems at scale in Java, Scala, Python or similar (not just R or Matlab)
You have a strong mathematical background in statistics and machine learning
You care about agile software processes, data-driven development, reliability, and responsible experimentation
You preferably have experience with data processing and storage frameworks like Hadoop, Scalding, Spark, Storm, Google Dataflow, Cassandra, Kafka, etc.
You preferably have machine learning publications or work on open source to share with us
We are proud to foster a workplace free from discrimination. We strongly 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.