We are looking for an Engineering Manager – Machine Learning with expertise in Machine Learning to join the User Engagement mission in New York. Our organization strives to make every user session amazing through personalization and discovery. In this role, you’ll work primarily with our squads based in New York who are focused on recommendations and personalized features (e.g. Discover Weekly, Release Radar, Daily Mix and Home), notifications and programming analytics.
What you’ll do
- You will serve a group of machine learning engineers and research scientists through hiring, coaching, mentoring, career development, and, when needed, hands-on engineering
- You will support those engineers and scientists in building upon Spotify’s deep understanding of our content, users, and artists to facilitate development of rich and engaging experiences
- You will provide technical mentorship in machine learning engineering and research topics including hypothesis testing, analysis, modeling, and production deployment, especially in a JVM ecosystem
- You will work closely with other machine learning Chapter Leads to continue to mature the use of machine learning in Spotify’s New York office and beyond
- You will be based in New York, but travel occasionally to our Stockholm office
Who you are
- Strong background in machine learning or a related field. Graduate education preferred.
- Experience giving hands-on leadership, whether formally or informally (e.g., mentoring), to individuals implementing machine learning systems at scale in Java, Scala, Python or similar languages
- You care about agile software processes, data-driven development, reliability, and disciplined experimentation
- You preferably have experience with high-scale data processing and storage frameworks like Hadoop, Scalding, Spark, Storm, Cassandra, Kafka, etc.
- You thrive when developing great people, not just great products
- You want to make a global impact and believe 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.