Spotify
Spotify19d ago

Staff Machine Learning Engineer, Home Podcast

Data ScienceOtherStaff Machine Learning EngineerMachine LearningData & AI
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Quick Summary

Overview

The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Blend to Discover Weekly, we’re behind some of Spotify’s most-loved features.

Technical Tools
Data ScienceOtherStaff Machine Learning EngineerMachine LearningData & AI

The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Blend to Discover Weekly, we’re behind some of Spotify’s most-loved features. We built them by understanding the world of music and podcasts better than anyone else. Join us and you’ll keep millions of users listening by making great recommendations to each and every one of them.

We are looking for a Staff MLE to join Surfaces Podcasts. The Surfaces Podcasts team builds the systems that power podcast recommendations across some of Spotify’s most visible experiences, including Home and the Now Playing view. We work across candidate generation, ranking, and embedding models to help listeners discover their favorite new podcast and engage deeply with their favorite shows.

We’re also shaping the next generation of personalization through transformer-based models that bring more dynamic, context-aware recommendations to millions of listeners. You’ll collaborate closely with teams across Personalization, Experience, and the Podcast Mission to evolve podcast listening across Spotify.



  • Contribute to designing, scaling/building, evaluating, integrating, shipping, and refining reward signals for recommendations by hands-on ML development
  • Promote and role-model best practices of ML systems development, testing, evaluation, etc., both inside the team as well as throughout the organization.
  • Lead collaborations and align across PZN to integrate and A/B test mid-term signals in various recommendation systems
  • You have a strong background in machine learning, enjoy applying theory to develop real-world applications, with expertise in statistics and optimization, especially in sequential models, transformers, generative AI and large language models, and relevant fine-tuning processes.
  • You have hands-on experience with large cross-collaborative machine learning projects and managing stakeholders.
  • You have hands-on experience implementing production machine learning systems at scale in Java, Scala, Python, or similar languages. Experience with PyTorch, Ray, Hugging Face and related tools is required.
  • You have some experience with large scale, distributed data processing frameworks/tools like Apache Beam, Apache Spark, or even our open source API for it - Scio, and cloud platforms like GCP or AWS.
  • You care about agile software processes, data-driven development, reliability, and disciplined experimentation.
  • We offer you the flexibility to work where you work best! For this role, you can be within North America as long as we have a work location.
  • This team operates within the Eastern Standard time zone for collaboration
  • Location & Eligibility

    Where is the job
    New York, United States
    Remote within one country
    Who can apply
    US
    Listed under
    United States

    Listing Details

    Posted
    April 15, 2026
    First seen
    April 15, 2026
    Last seen
    May 5, 2026

    Posting Health

    Days active
    19
    Repost count
    0
    Trust Level
    44%
    Scored at
    May 5, 2026

    Signal breakdown

    freshnesssource trustcontent trustemployer trust
    Spotify
    Spotify
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    Our mission is to unlock the potential of human creativity—by giving a million creative artists the opportunity to live off their art and billions of fans the opportunity to enjoy and be inspired by it.

    Employees
    3k+
    Founded
    2006
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    SpotifyStaff Machine Learning Engineer, Home Podcast