Description:

The Now Playing View team at Spotify is focused on creating a new surface that allows users to engage deeply with the content they are currently playing and explore related content.
This role involves working with content such as concerts, lyrics, merchandise, and playable recommendations like music, podcasts, and audiobooks.
The team is looking for a Senior Machine Learning Engineer to help scale and personalize recommendations on this surface.
As a founding Machine Learning engineer, you will be responsible for training and deploying the first models for the NPV surface across Music, Podcasts, and Audiobooks.
You will collaborate closely with Backend and Data engineers to meet latency requirements for model serving and work with the Engineering Manager and Product Manager to shape the Machine Learning strategy.
Responsibilities include coordinating technical projects, facilitating collaboration across teams, and being a valued member of an autonomous, cross-functional agile team.
You will architect, design, develop, and deploy Machine Learning models for real-time recommendations and lead the personalization Machine Learning community.

Requirements:

You must have experience as a technical leader or mentor.
A strong background in machine learning is required, with expertise in personalized machine learning algorithms, particularly recommender systems.
Experience with Spotify-kubeflow and Salem is preferred.
You should be experienced in feature engineering and building scalable data pipelines using Scio.
A deep understanding of Machine Learning systems and infrastructure is necessary.
Proficiency in TensorFlow or Keras is required.
You should be able to implement end-to-end production ML systems at scale using Java, Scala, Python, or similar languages.

The position offers a competitive salary range of $176,166 to $251,666, plus equity.
Benefits include health insurance and a six-month paid parental leave.
A 401(k) retirement plan is provided.
Employees receive a monthly meal allowance.
The role includes 23 paid days off and 13 paid flexible holidays.
Paid sick leave is also available.