Description:

The Personalization (PZN) team at Spotify aims to enhance the listening experience by making it easier and more enjoyable for users to decide what to play next.
The team focuses on understanding music, podcasts, and audiobooks to provide personalized recommendations to listeners.
Responsibilities include designing, building, evaluating, and shipping machine learning (ML) solutions for Spotify’s personalization products.
Collaboration with cross-functional teams, including user research, design, data science, product management, and engineering, is essential to develop new product features.
The role involves prototyping new approaches and scaling solutions for hundreds of millions of active users.
Promoting best practices in ML systems development, testing, and evaluation is expected both within the team and across the organization.
The position is part of a vibrant community of machine learning practitioners.

Requirements:

Candidates should be experienced ML practitioners with a motivation to tackle complex real-world problems in a fast-paced, collaborative environment.
A strong background in machine learning, natural language processing, and generative AI is required, along with experience in applying theory to real-world applications.
Hands-on expertise in implementing end-to-end production ML systems at scale using Python, Java, or Scala is necessary.
Experience with Pytorch and/or TensorFlow is considered a strong plus.
Candidates should have experience in designing end-to-end tech specifications and modular architectures for ML frameworks in collaboration with product teams.
Familiarity with large-scale, distributed data processing frameworks/tools like Apache Beam, Apache Spark, and cloud platforms such as GCP or AWS is required.

Spotify offers flexibility in work location within the European region, excluding France due to on-call restrictions.
The team operates within the GMT/CET time zone for collaboration.
Spotify is committed to inclusivity and provides reasonable accommodations during the recruitment process to support all candidates.
The company values diversity and encourages applicants to bring their personal experiences and perspectives to foster a thriving workplace.