Job Post

Engineering Manager - Personalization Platform

Spotify
48 Grove Street
Somerville, MA 02144

We need an Engineering Manager (Chapter Lead) in Boston with expertise in high-scale, machine-learning-driven systems to give management to engineers and leadership to teams in our Personalization Platform product area. The Personalization Platform helps power Spotifys personalized features whether listening experiences like Discover Weekly and Daily Mix or means of exploration like Search and Home. It is built by technologists, product insight experts, designers, and product managers in both Boston and New York, with customers in those offices as well as Stockholm and London.

What youll do

  • Serve a group of engineers as manager through hiring, coaching, mentoring and career development
  • Be a leader of one or more teams, taking accountability for delivery and technological health. This happens through technological coaching in everything from architectural vision to operational excellence and through collaboration with product management in setting and executing against the right goals
  • Give leadership to other efforts that fit your passion and Spotify's needs in collaboration with other managers and engineers in the product area, tribe, mission or across Spotify

Who you are

  • You thrive when helping individuals develop to be their best
  • You are passionate about creative, high-scale, machine-learning driven products and the substantial challenges they can address, especially Spotify's mission to unlock the potential of human creativity
  • You love staying up-to-date with the state-of-the-art in machine learning and/or distributed systems through review of research
  • You understand the value of agile development in enabling highly effective teams

We are proud to foster a workplace free from discrimination. We strongly believe that diversity of experience, perspectives, and background will lead to a better environment for our employees and a better product for our users and our creators. This is something we value deeply and we encourage everyone to come be a part of changing the way the world listens to music.

Category: Data Science / Machine Learning
Full-time

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