Engineering Role: Machine Learning Engineer Personalization London
Engineering Role: Machine Learning Engineer Personalization London

Engineering Role: Machine Learning Engineer Personalization London

London Full-Time 43200 - 72000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Join our team to enhance user experience through innovative machine learning solutions.
  • Company: Spotify is the leading audio streaming service, revolutionising how we enjoy music and podcasts.
  • Benefits: Enjoy flexible work options, extensive learning opportunities, and generous parental leave.
  • Why this job: Be part of a passionate team that shapes the future of music recommendations for millions.
  • Qualifications: Experience in applied machine learning and proficiency in Python required; cloud platform knowledge is a plus.
  • Other info: We value diversity and inclusivity, welcoming unique perspectives to drive innovation.

The predicted salary is between 43200 - 72000 £ per year.

The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Blend 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 are looking for a Machine Learning Engineer (MLE II) to join our product area of hardworking engineers that are passionate about connecting new and emerging creators with users via recommendation algorithms. As an integral part of the squad, you will collaborate with engineers, research scientists, and data engineers in prototyping and productizing state-of-the-art ML models that allow us to find the right audience for content that is strategically important, such as fresh or timely content.

What You’ll Do

  • Develop and implement production systems that enrich and improve our listeners’ experience on the platform.
  • Contribute to designing, building, evaluating, shipping, and refining Spotify’s product by hands-on ML development.
  • Help drive optimization, testing, and tooling to improve quality of our recommendations.
  • Perform data analysis to establish baselines and inform product decisions.
  • Collaborate with a cross functional agile team spanning tech research, data science, product management, and engineering to build new technologies and features.
  • Stay up-to-date on the latest machine learning algorithms and techniques.

Who You Are

  • You have professional experience in applied machine learning.
  • Extensive experience working in a product and data-driven environment (Python, Scala, Java, SQL, or C++, with Python experience required) and cloud platforms (GCP or AWS).
  • You have some hands-on experience implementing or prototyping machine learning systems at scale.
  • You have experience architecting data pipelines and are self-sufficient in getting the data you need to build and evaluate models, using tools like Dataflow, Apache Beam, or Spark.
  • You care about agile software processes, data-driven development, reliability, and disciplined experimentation.
  • You have experience and passion for fostering collaborative teams.
  • Experience with TensorFlow, pyTorch, and/or other scalable Machine learning frameworks.
  • Experience with building data pipelines and getting the data you need to build and evaluate your models, using tools like Apache Beam / Spark.

Where You’ll Be

We offer you the flexibility to work where you work best! For this role, you can be within the EMEA region as long as we have a work location (excluding France due to on-call restrictions). This team operates within the Central European and GMT time zone for collaboration.

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.

Engineering Role: Machine Learning Engineer Personalization London employer: Spotify AB

At Spotify, we pride ourselves on being an exceptional employer, particularly for the Machine Learning Engineer role in London. Our vibrant work culture fosters collaboration and innovation, allowing you to contribute to beloved features that enhance user experience while enjoying extensive learning opportunities through our dedicated GreenHouse team. With flexible working arrangements, generous parental leave, and a commitment to inclusivity, we ensure that every employee feels valued and empowered to grow within a dynamic environment.
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Contact Detail:

Spotify AB Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Engineering Role: Machine Learning Engineer Personalization London

✨Tip Number 1

Familiarise yourself with Spotify's key features like Blend and Discover Weekly. Understanding how these features work will help you demonstrate your knowledge of the product during interviews.

✨Tip Number 2

Showcase your experience with machine learning frameworks such as TensorFlow or PyTorch. Be prepared to discuss specific projects where you've implemented these technologies, as practical examples can set you apart.

✨Tip Number 3

Highlight your collaborative skills by discussing past experiences working in cross-functional teams. Spotify values teamwork, so sharing how you've successfully collaborated with engineers and data scientists will be beneficial.

✨Tip Number 4

Stay updated on the latest trends in machine learning and data analysis. Being able to discuss recent advancements or techniques can show your passion for the field and your commitment to continuous learning.

We think you need these skills to ace Engineering Role: Machine Learning Engineer Personalization London

Applied Machine Learning
Python Programming
Data Analysis
Machine Learning Frameworks (TensorFlow, PyTorch)
Cloud Platforms (GCP, AWS)
Data Pipeline Architecture
Agile Software Development
Collaboration and Teamwork
Prototyping Machine Learning Systems
SQL
Scala or Java or C++
Dataflow, Apache Beam, or Spark
Optimization and Testing
Product and Data-Driven Environment Experience

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights relevant experience in machine learning and software development. Focus on projects where you've implemented ML systems, especially using Python, and mention any experience with cloud platforms like GCP or AWS.

Craft a Compelling Cover Letter: In your cover letter, express your passion for music and podcasts, and how it aligns with the role. Discuss your experience in collaborative environments and your approach to data-driven development, showcasing your understanding of the company's mission.

Showcase Technical Skills: Clearly list your technical skills related to the job description, such as proficiency in Python, experience with TensorFlow or PyTorch, and familiarity with data pipeline tools like Apache Beam or Spark. Provide examples of how you've used these skills in past roles.

Highlight Collaborative Experience: Emphasise your experience working in cross-functional teams. Mention specific instances where you collaborated with engineers, data scientists, or product managers to achieve project goals, as this is crucial for the role.

How to prepare for a job interview at Spotify AB

✨Showcase Your Technical Skills

Be prepared to discuss your experience with machine learning frameworks like TensorFlow and PyTorch. Bring examples of projects where you've implemented ML systems, and be ready to explain your thought process and the challenges you faced.

✨Understand the Product

Familiarise yourself with Spotify's features, especially those related to personalisation like Discover Weekly and Blend. Demonstrating knowledge about how these features work and their impact on user experience will show your genuine interest in the role.

✨Collaborative Mindset

Since the role involves working with cross-functional teams, highlight your experience in collaborative environments. Share examples of how you've successfully worked with engineers, data scientists, and product managers to achieve common goals.

✨Stay Current with Trends

Keep up-to-date with the latest trends in machine learning and data analysis. Be ready to discuss recent advancements or techniques that could benefit Spotify's recommendation algorithms, showing that you're proactive and passionate about the field.

Engineering Role: Machine Learning Engineer Personalization London
Spotify AB
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  • Engineering Role: Machine Learning Engineer Personalization London

    London
    Full-Time
    43200 - 72000 £ / year (est.)

    Application deadline: 2027-06-10

  • S

    Spotify AB

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