Machine Learning Engineer, GenRecs, Personalization

Spotify; London; Remote; GBP 60,000 - 90,000; Full time

Job summary

A leading audio streaming service is seeking an experienced Machine Learning Practitioner to enhance personalization features. The role involves designing and implementing advanced ML solutions while collaborating across teams to drive innovative recommendations for millions of users. This position offers flexibility in work location within the European region.

Qualifications

• Experienced ML practitioner capable of solving complex problems.
• Hands-on experience with large scale ML systems.
• Background in collaborative environments and various ML frameworks.

Responsibilities

• Design and ship ML solutions.
• Collaborate with cross-functional teams.
• Prototype new approaches at scale.

Skills

Machine Learning

Natural Language Processing

Generative AI

Collaboration

End-to-end ML systems

Education

Experience in ML

Tools

Python

Java

Scala

Pytorch

TensorFlow

Apache Beam

Apache Spark

GCP

AWS

Job description

The Personalization (PZN) team makes deciding what to play next on Spotify easier and more enjoyable for every listener. We seek to understand the world of music, podcasts and audiobooks better than anyone else so that we can make great recommendations to every individual and keep the world listening. Every day, hundreds of millions of people all over the world use the products we build which include destinations like Home and Search as well as original playlists such as Made For You, Discover Weekly and Daily Mix.

What You'll Do

• Design, build, evaluate, and ship ML solutions in Spotify’s personalization products
• Collaborate with cross functional teams 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 useful ways
• Prototype new approaches and productionize solutions at scale for our hundreds of millions of active users
• Promote and role-model best practices of ML systems development, testing, evaluation, etc., both inside the team as well as throughout the organization
• Be part of an active group of machine learning practitioners

Who You Are

• An experienced ML practitioner motivated to work on complex real-world problems in a fast-paced and collaborative environment
• Strong background in machine learning, natural language processing, and generative AI, with experience in applying theory to develop real-world applications
• Hands-on expertise with implementing end-to-end production ML systems at scale in Python, Java or Scala
• Experience with Pytorch and/or TensorFlow is a strong plusExperience with designing end-to-end tech specs and modular architectures for ML frameworks in complex problem spaces in collaboration with product teams
• Experience with large scale, distributed data processing frameworks/tools like Apache Beam, Apache Spark, and cloud platforms like GCP or AWS

Where You'll Be

• We offer you the flexibility to work where you work best! For this role, you can be within the European region as long as we havea work location.
• This team operates within the GMT/CET time zone for collaboration.
• Excluding France due to on-call restrictions.

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.