Staff Machine Learning Engineer – Home Ranking


  • Full Time

The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Daily Mix 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 squads 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 Staff 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 collaborate with research scientists, data scientists and other engineers in prototyping and productizing the state-of-the-art ML behind the Spotify Homepage recommendations to contribute to great listening experiences and the long-term user satisfaction of the 380+ million Spotify users. For the purposes of collaboration, we ask that our team members operate between the Eastern and Central European time zones. 


What You’ll Do


  • Prototype new ML approaches for scoring or ranking content and productize solutions at scale
  • Build new product features that inform and enrich Spotify’s various recommendation surfaces by collaborating with engineering stakeholders and colleagues in large cross-functional efforts
  • Promote and role-model best practices of ML model development, testing evaluation, and act as a mentor to others, both inside the team as well as throughout the organization
  • Be part of an active group of machine learning practitioners across Spotify collaborating with one another

    Who You Are


  • You have ample experience in machine learning research, in fields such as recommendation systems, ranking and relevance, reinforcement learning, causal ML and/or probability theory and statistics. You enjoy applying theory to develop real-world applications 
  • You have a Master’s or PhD in ML, statistics, or an engineering field with 5+ years of experience 
  • 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, PyTorch, or scikit-learn is a strong plus
  • You are a self-starter who drives your own projects and builds strong relationships with stakeholders and colleagues to tackle large cross-functional efforts from start to finish, collaborating with our research partners in Tech Research along the way. You are able to thrive with minimal guidance and process
  • You have experience with agile software processes and modular code design following best practices

    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 or European regions in which we have a work location and is within working hours
  • Working hours? We operate between the Eastern and Central European time zones for collaboration
  • 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



    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.