Spotify

Senior Machine Learning Engineer

Spotify New York, NY

Home Ranking is responsible for creating a personalized Home for every user via an ML ranking system. We take candidates (e.g., playlists, podcast shows, audiobooks) and use various user, content, and context features to determine what will maximize a user’s engagement.

What You'll Do

  • Improve the ranking system to incorporate the best data and features to improve recommendations on Home (for all 615+ million users!)
  • Develop ranking system iterations based on tests, learnings, and published research
  • Lots of online experimentation with hundreds of millions of users and high-impact metrics

Who You Are

  • You have ample experience in machine learning, in fields such as recommendation systems or ranking and relevance
  • You have applied knowledge of A/B testing for model evaluation
  • You have hands-on experience implementing production machine learning systems at scale in Python, Java, or similar languages
  • Experience with tools like TensorFlow or PyTorch
  • You have experience with agile software processes and modular code design following industry standards

Where You'll Be

  • We are a distributed workforce enabling our band members to find a work mode that is best for them!Working hours? We operate in the Eastern US time zone for collaboration
  • Where in the world? For this role, it can be within the Americas as long as your working hours are aligned with the Eastern US
  • Prefer an office to work from home instead? Not a problem!
  • We have plenty of options for your working preferences
  • Find more information about our Work From Anywhere options here

The United States base range for this position is $171,903- 245,575 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, paid sick leave. These ranges may be modified in the future.

#JobSite-Sub-MachineLearning

Today, we are the world’s most popular audio streaming subscription service.
  • Seniority level

    Mid-Senior level
  • Employment type

    Full-time
  • Job function

    Engineering
  • Industries

    Musicians

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