Machine Learning Engineer - User Fraud

New Yesterday

We are seeking a Machine Learning Engineer to join the User Fraud R&D Studio at Spotify. Our mission is to protect Spotify from fake accounts and artificial streaming.

You’ll work in a fast-moving team that experiments, iterates, and deploys innovative fraud prevention solutions. This includes analysing diverse user behaviours, uncovering patterns of abuse, and developing robust, scalable ML models that power real-time and batch decisions.

If you're excited by adversarial modelling, anomaly detection, and building systems that defend one of the world's leading streaming platforms, we'd love to hear from you.


What You'll DoWho You AreWhere You'll Be

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.

At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we’re here to support you in any way we can.

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.

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Location:
London, England, United Kingdom
Salary:
£200,000 +
Category:
Engineering

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