What you’ll do
- Apply machine learning methods to massive data sets to extend and enhance Spotify’s means of understanding and engaging users across various contexts and modalities
- Prototype new algorithms and production-ize solutions at scale
- Collaborate with a cross-functional agile team of back end engineers, data engineers, front-end engineers, and other ML experts
- Iterate on quality through offline and online testing
- Be part of an active group of machine learners in Boston (and across Spotify) learning from and encouraging one another
- Work from our office in Boston (Davis Square) with opportunity to travel to New York and Stockholm
Who you are
- Strong background in Machine Learning or a related field. Significant expertise in personalized machine learning algorithms, recommender systems, understanding of natural language or other unstructured data, or deep learning is a plus.
- 2-3 years or more in industry on a team implementing machine learning systems in Java, Scala, Python or similar languages (not just R or Matlab, as cool as those can be :-)
- You care about agile software processes, data-driven development, reliability, and disciplined experimentation
- You preferably have experience with data pipeline and storage frameworks like BigQuery, Hadoop, Scio, Spark, Cassandra, Kafka, etc.
- You’re motivated by the belief that music improves lives.
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.