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Machine Learning Engineer

AT Spotify
Spotify

Machine Learning Engineer

London, United Kingdom

We in the Machine Learning product area in the Activation, Retention, Conversion studio are focused on building robust and scalable machine learning solutions that can personalize activation, retention and conversion funnels to improve important business metrics like SUBS and MAU. Through our messaging platform as well as other discovery & conversion surfaces, we communicate with users to connect them with valuable audio content and to help the business grow.

Our vision is to build the machine learning models and infrastructure that offers a fully personalized and ML-optimized experience for listeners throughout their user journey that powers every messaging and conversion campaign at Spotify.

This role sits in a squad called White Mouse that owns the optimization of plan upsell targeting across Spotify. Our key problem areas are: What plan should the user be upsold on discovery surfaces? How should we communicate the user on consideration surfaces? How should we balance upselling plans vs other paid products?

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What You'll Do

  • Contribute to designing, building, evaluating, shipping, and refining Spotify's product by hands-on ML development
  • Collaborate with a multi-functional agile team spanning user research, design, 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 productionize solutions at scale for our hundreds of millions of active users
  • Help drive optimisation, testing, and tooling to improve quality
  • Be part of an active group of machine learning practitioners in your mission and across Spotify

Who You Are

  • You have a strong background in machine learning, theory, and practice
  • You are comfortable explaining the intuition and assumptions behind ML concepts
  • You have hands-on experience implementing and maintaining production ML systems in Python, Scala, or similar languages
  • Experience with TensorFlow is also a plus
  • You are experienced with building data pipelines, and you are self-sufficient in getting the data you need to build and evaluate your models
  • You preferably have experience with cloud platforms like GCP or AWS
  • You care about agile software processes, data development, reliability, and focused experimentation
  • You have a desire to drive business impact

Where You'll Be

  • This role will be located in our London or Stockholm office

Our global benefits

Extensive learning opportunities, through our dedicated team, GreenHouse.

Flexible share incentives letting you choose how you share in our success.

Global parental leave, six months off - fully paid - for all new parents.

All The Feels, our employee assistance program and self-care hub.

Flexible public holidays, swap days off according to your values and beliefs.

Learn about life at Spotify

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 with a community of more than 500 million users.

Client-provided location(s): London, UK; Stockholm, Sweden
Job ID: Spotify-75fb84f2-fdfd-4738-986f-b9c8622491f9
Employment Type: Other