Senior Machine Learning Engineer

What You'll Do

• 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.

Who You Are

• You have experience building, deploying, and improving machine learning systems in production environments.
• You have a strong understanding of machine learning approaches for information retrieval, search ranking, recommendation systems, or personalization.
• You are proficient in Python and comfortable working with modern machine learning frameworks and data processing tools.
• You have experience and a desire to lean into backend engineering at Spotify scale.
• You understand how to design and evaluate experiments, interpret model performance, and translate technical findings into product improvements.
• You have experience working with large-scale datasets and understand the challenges of building reliable, scalable machine learning systems.
• You are curious about emerging AI technologies, including large language models and agentic systems, and interested in their potential to improve discovery experiences.
• You enjoy working across disciplines, communicating technical ideas clearly, and learning from different perspectives.
• You are comfortable navigating ambiguity, taking ownership of complex challenges, and balancing experimentation with practical delivery.