Senior Machine Learning Engineer, Personalization

The Personalization team at Spotify makes deciding what to play next easier and more enjoyable for every listener. We're behind some of Spotify's most-loved features, such as Blend and Discover Weekly. As a Senior Machine Learning Engineer in the Growlithe squad, you will work at the intersection of machine learning, personalization, and product development, turning complex challenges into intuitive discovery experiences for millions of listeners.

Responsibilities

• Build and improve machine learning models that make Spotify Search more relevant, personalized, and engaging for listeners.
• Develop and optimize ranking and backend retrieval systems that help listeners discover music, videos, audiobooks, and other content.
• Explore emerging AI and agentic approaches to create more intuitive and conversational Search experiences.
• Design, implement, and evaluate machine learning solutions, taking ideas from early experimentation through production.
• Partner with engineers, product managers, designers, and researchers to identify opportunities and deliver meaningful improvements to Search.
• Use experimentation, data analysis, and performance metrics to understand model behavior, validate hypotheses, and improve the listener experience.
• Contribute to scalable machine learning infrastructure and engineering practices that support reliable, high-quality Search experiences.
• Share knowledge, challenge assumptions constructively, and help shape the technical direction of machine learning within the squad.

Requirements

• Experience building, deploying, and improving machine learning systems in production environments.
• Strong understanding of machine learning approaches for information retrieval, search ranking, recommendation systems, or personalization.
• Proficiency in Python and experience with modern machine learning frameworks and data processing tools.
• Experience with backend engineering at scale.
• Understanding of how to design and evaluate experiments, interpret model performance, and translate technical findings into product improvements.
• Experience working with large-scale datasets and building reliable, scalable machine learning systems.
• Curiosity about emerging AI technologies, including large language models and agentic systems.
• Enjoy working across disciplines, communicating technical ideas clearly, and learning from different perspectives.
• Comfortable navigating ambiguity, taking ownership of complex challenges, and balancing experimentation with practical delivery.

Location and Benefits

• This role is based in Eastern Standard Time and offers flexible work arrangements, including remote work options.
• The United States base range for this position is $184,049–$262,928 USD, plus equity.
• Benefits include health insurance, six-month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, paid flexible holidays, and paid sick leave.