Remote Machine Learning Engineer - User Fraud

Spotify
Wakefield, UK
2 months ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Job source

Tech stack

Agile Methodology Amazon Web Services Database Development Python (Programming Language) Machine Learning Tensorflow Pytorch Machine Learning Operations Data Pipelines

Job description

  • Contribute to designing, building, evaluating, shipping, and refining Spotify’s anti-fraud product by hands-on ML development
  • Collaborate with a multi-functional team spanning data science, product management, and engineering to combat fraud
  • Prototype new approaches and productionise solutions
  • 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
  • Conduct analyses to gain insights on fraudulent behaviours and trends
  • Be responsible for monitoring the quality and performance of the squad’s ML models

Requirements

  • 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 languagesExperience with TensorFlow or Pytorch
  • You are experienced with building data pipelines, and you are self-sufficient in getting the data you need to build and evaluate your modelsYou preferably have experience with cloud platforms like GCP or AWS
  • You care about agile software processes, data development, reliability, and focused experimentation
  • You focus on delivering the simplest solution that drives business impact

About the company

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., * This role is based in Stockholm, Sweden or London, United Kingdom

  • We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home.

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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