Machine Learning Engineer, Home Ranking & Assembly, Personalization

Spotify

  • Full Time

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 ask that our team members be physically located in Central European time or Eastern Standard/Daylight time zones for the purposes of our collaboration hours.

The Home Ranking & Home Assembly teams within Spotify’s Personalization Mission, focus on what to recommend on Spotify’s Homepage and where, by building the models to rank and find the perfect content mix and position for all music & podcast content, fully tailored to each user. We are looking for a Machine Learning Engineer who is passionate for personalization ML models, recommender systems and disciplines included but not limited to contextual bandits, causal ML, deep learning, and reinforcement learning, which are actively used and expanded by our teams. Join us and you’ll keep millions of users listening by making great recommendations to the Spotify Homepage of each and every one of them. For the purposes of collaboration, we ask that our team members operate between the Eastern and Central European time zones.

 

What you’ll do

 

  • Design, build, evaluate, ship, and refine Spotify’s product by hands-on ML development
  • Collaborate with a cross functional agile team spanning research, data science, product management, and engineering to build new product features that advance our mission to connect artists and fans in personalized and relevant ways
  • Prototype new approaches and production-ize solutions at scale for our hundreds of millions of active users
  • Help drive optimization, testing, and tooling to improve quality
  • Be part of an active group of machine learning practitioners across Spotify, collaborating with one another.
  •  

    Who you are

     

  • You have a strong background in machine learning, with experience and expertise in personalized machine learning algorithms, especially recommender systems
  • Experience with contextual bandits, causal ML, deep learning, or reinforcement learning is a plus
  • You have hands-on experience implementing production machine learning systems at scale in Java, Scala, Python, or similar languages. Experience with XGBoost, TensorFlow is also a plus
  • You care about agile software processes, data-driven development, reliability, and disciplined experimentation.
  •  

    Where you’ll be

     

  • We are a distributed workforce enabling our band members to find a work mode that is best for them!
  • Where in the world? For this role, it can be within the Americas region in which we have a work location
  • We ask that our team members be located within Central Standard time zone, Eastern Standard time zone, or Brasília time zone for the purposes of our collaboration hours
  • 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.
  • Working hours? We operate within the Eastern Standard time zone for collaboration
  •  

     

     

    Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens.
    Spotify transformed music listening forever when we launched in 2008. 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 chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world’s most popular audio streaming subscription service.
    Global COVID and Vaccination Disclosure
    Spotify is committed to safety and well-being of our employees, vendors and clients. We are following regional guidelines mandating vaccination and testing requirements, including those requiring vaccinations and testing for in-person roles and event attendance. For the US, we have mandated that all employees and contractors be fully vaccinated in order to work in our offices and externally with any third-parties. For all other locations, we strongly encourage our employees to get vaccinated and also follow local COVID and safety protocols.