Another position to aspire towards to. The qualifications gives me an idea what subject matters that I have to deeply learn[pun intended :)]. Combine this and the Pandora position, has given me a clearer picture of what a “music scientist” need to be fluent in.

Machine Learning Engineer @ Spotify.

What you’ll do

  • Apply machine learning methods to massive data sets
  • Prototype new algorithms, evaluate with small scale experiments, and later production-ize solutions at scale to our over 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
  • Be part of an active group of machine learners in Boston (and across Spotify) learning from and encouraging one another
  • Iterate on quality through continuous A/B testing
  • Work from our office in Boston (Davis Square)

Who you are

  • Masters or strong undergraduate education in Machine Learning, or related field *I can’t afford school, so “pet projects” are important!
  • You have experience implementing machine learning systems at scale in Java, Scala, Python or similar languages (not just R or Matlab)
  • You care about agile software processes, data-driven development, reliability, and disciplined experimentation
  • You preferably have experience with data processing and storage frameworks like Hadoop, Scalding, Spark, Storm, Cassandra, Kafka, etc.

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.

Machine Learning Engineer at Spotify: a Music Scientist job description part 2.

Category: Notes