Spotify-posted about 1 month ago
Full-time • Senior
Remote • New York, NY
5,001-10,000 employees

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, podcasts, and audiobooks 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 Senior Machine Learning Engineer to join the Personalization team - an area of hardworking engineers that are passionate about understanding what drives user satisfaction with Spotify - and who make impactful changes to recommendation systems to achieve this goal. As an integral part of the squad, you will collaborate with research scientists, data scientists and other engineers across PZN in prototyping and productizing state-of-the-art ML at the intersection of recommendations and long-term user satisfaction.

  • Contribute to designing, scaling/building, evaluating, integrating, shipping, and refining ML models for the personalization of the main homepage
  • Lead collaborations and align across PZN to integrate and A/B test mid-term signals in various recommendation systems
  • Promote and role-model best practices of ML systems development, testing, evaluation, etc., both inside the team as well as throughout the organization.
  • 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, transformer architecture models, and fine-tuning processes for sequential models
  • 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
  • You care about agile software processes, data-driven development, reliability, and disciplined experimentation.
  • Experience with TensorFlow, PyTorch, Scikit-learn, etc. is a strong plus
  • 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
  • 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
© 2024 Teal Labs, Inc
Privacy PolicyTerms of Service