At a Glance
- Tasks: Join a dynamic team to develop innovative fraud prevention solutions for Spotify.
- Company: Spotify is the world's leading audio streaming service, passionate about music and creativity.
- Benefits: Enjoy flexible work options, including remote work and a supportive environment.
- Why this job: Make a real impact by combating fraud on a global platform while collaborating with diverse teams.
- Qualifications: Strong machine learning background with hands-on experience in Python or Scala; familiarity with TensorFlow or Pytorch.
- Other info: Inclusive workplace that values diversity and offers support throughout the recruitment process.
The predicted salary is between 28800 - 48000 £ per year.
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 Do
- 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
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 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
Where You\’ll Be
- 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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Machine Learning Engineer - User Fraud employer: Spotify
Contact Detail:
Spotify Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer - User Fraud
✨Tip Number 1
Familiarise yourself with Spotify's current anti-fraud measures and technologies. Understanding their existing systems will not only help you in interviews but also demonstrate your genuine interest in the role and the company.
✨Tip Number 2
Engage with the machine learning community, particularly those focused on fraud detection and anomaly detection. Participating in relevant forums or attending meetups can provide insights and connections that may be beneficial during the application process.
✨Tip Number 3
Showcase your hands-on experience with ML frameworks like TensorFlow or PyTorch through personal projects or contributions to open-source. This practical demonstration of your skills can set you apart from other candidates.
✨Tip Number 4
Prepare to discuss specific examples of how you've tackled challenges in previous roles, especially related to building data pipelines or optimising ML models. Real-world examples will illustrate your problem-solving abilities and technical expertise.
We think you need these skills to ace Machine Learning Engineer - User Fraud
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, particularly any hands-on work with production ML systems. Emphasise your familiarity with Python, Scala, TensorFlow, or PyTorch, as well as any experience with cloud platforms like GCP or AWS.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for combating user fraud and your understanding of the challenges involved. Mention specific projects or experiences that demonstrate your ability to analyse user behaviours and develop scalable ML models.
Showcase Your Projects: If you have worked on relevant projects, consider including links to your GitHub or portfolio. Highlight any prototypes or solutions you've developed that relate to fraud prevention or anomaly detection, showcasing your practical skills.
Prepare for Technical Questions: Be ready to discuss your understanding of machine learning concepts and your previous experiences in detail. Prepare to explain the intuition behind your approaches and how you’ve implemented them in real-world scenarios, especially in relation to fraud detection.
How to prepare for a job interview at Spotify
✨Showcase Your ML Knowledge
Be prepared to discuss your understanding of machine learning concepts, especially those relevant to fraud detection. Highlight your experience with adversarial modelling and anomaly detection, as these are key areas for the role.
✨Demonstrate Practical Experience
Share specific examples of your hands-on experience with production ML systems. Discuss projects where you implemented models using Python, Scala, TensorFlow, or PyTorch, and how you overcame challenges in those projects.
✨Collaborative Mindset
Emphasise your ability to work within a multi-functional team. Be ready to talk about how you've collaborated with data scientists, product managers, and engineers in the past to achieve common goals, particularly in combating fraud.
✨Focus on Impact
Prepare to discuss how your work has driven business impact in previous roles. Spotify values simplicity and effectiveness, so be ready to explain how you prioritised solutions that delivered tangible results.