The Now Playing View team is a new surface on Spotify that gives users a chance to engage deeply with the content they are currently playing and explore new content related to what’s currently playing. With content like concerts, lyrics, and merchandise, as well as playable recommendations like music, podcasts, and audiobooks, there is a huge opportunity to scale and personalize recommendations on the surface.
The Home NPV team, which is taking ownership of this surface, is looking for a Senior Machine Learning Engineer to join a team of talented engineers that share a common interest in distributed systems, scalability, and Machine Learning best practices. As one of the founding Machine Learning engineers on the team, you will be responsible for training and deploying the first models to power the NPV surface across Music, Podcasts, and Audiobooks. You will work closely with the Backend and Data engineers on the team to ensure we meet latency requirements for serving the model on the request path, as well as work closely with the Engineering Manager and Product Manager to drive the future of the Machine Learning strategy.
What You'll Do
- Coordinate technical projects across teams within Spotify
- Facilitate collaboration with other engineers, product owners, and designers to solve interesting and challenging problems for delivering various media worldwide
- Be a valued member of an autonomous, cross-functional agile team
- Architect, design, develop, and deploy the first Machine Learning models that will serve real-time recommendations across the Music, Podcast, and Audiobook NPV surfaces.
- Be a leader in personalization's Machine Learning community and work collaboratively and efficiently within Home’s existing platforms and systems.
- Hands-on expertise with implementing end-to-end production ML systems at scale in Java, Scala, Python, or similar languages
- Help drive optimization, testing, and tooling to improve quality
Who You Are
- You have experience being a technical leader or mentor
- You have a strong background in machine learning, with experience and expertise in personalized machine learning algorithms, especially recommender systems (including experience in spotify-kubeflow and salem)
- You are experienced with feature engineering and building scalable data pipelines in Scio.
- You have a deep understanding of Machine Learning systems and infrastructure.
- You have experience in TensorFlow or Keras.
Where You'll Be
- We offer you the flexibility to work where you work best! For this role, you can be within the North America region as long as we havea work location.
- This team operates within the Eastern Standard Time zone for collaboration.
The United States base range for this position is $176,166 - $251,666 plus equity. The benefits available for this position include health insurance, six-month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, 13 paid flexible holidays, and paid sick leave. These ranges may be modified in the future.
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