Staff Machine Learning Engineer, Home Podcast

Spotify Spotify · Consumer · New York, NY · Personalization

Staff Machine Learning Engineer for Spotify's Home Podcast team, focusing on building and scaling podcast recommendation systems. The role involves hands-on ML development, including designing, evaluating, integrating, and refining reward signals for recommendations, with a focus on transformer-based models and A/B testing.

What you'd actually do

  1. Contribute to designing, scaling/building, evaluating, integrating, shipping, and refining reward signals for recommendations by hands-on ML development
  2. Promote and role-model best practices of ML systems development, testing, evaluation, etc., both inside the team as well as throughout the organization.
  3. Lead collaborations and align across PZN to integrate and A/B test mid-term signals in various recommendation systems

Skills

Required

  • Machine Learning
  • Recommendation Systems
  • Transformer Models
  • A/B Testing
  • ML Systems Development

Nice to have

  • Podcast Recommendations
  • Candidate Generation
  • Ranking Models
  • Embedding Models

What the JD emphasized

  • scaling/building
  • evaluating
  • integrating
  • shipping
  • refining
  • recommendations
  • ML systems development
  • testing
  • evaluation
  • A/B test

Other signals

  • Transformer-based models
  • Candidate generation, ranking, and embedding models
  • Podcast recommendations