Senior Machine Learning Engineer - Personalization, Horizon

About the Role

The Personalization team at Spotify is dedicated to enhancing the listening experience by making it easier and more enjoyable for users to discover their next favorite song or podcast. We are responsible for beloved features like Blend and Discover Weekly, developed through a deep understanding of music and podcasts. Join us to help millions of users stay engaged by delivering exceptional recommendations.

You will be part of the Horizon Product Area within the Sessions Studio, contributing to Spotify's Personalization Mission. This team pioneers and refines new listening experiences using emerging technologies, including AI DJ, promptable playlists, and generated podcasts. Your work will focus on the intersection of product innovation and advanced machine learning to create novel audio experiences for a vast user base.

What You'll Do

• Design, build, evaluate, and deploy agentic-based features and interactive experiences to elevate our products.
• Collaborate with cross-functional teams (user research, design, data science, product management, engineering) to develop new product features that align with our mission of connecting artists and fans in personalized and meaningful ways.
• Prototype innovative approaches and productionize scalable solutions for hundreds of millions of active users.
• Champion and exemplify best practices in ML systems development, testing, and evaluation within the team and across the organization.
• Contribute actively to Spotify's vibrant community of machine learning practitioners.

Who You Are

• Possess a strong foundation in machine learning, natural language processing, and generative AI, with a proven ability to apply theoretical knowledge to real-world applications.
• Demonstrate hands-on expertise in implementing end-to-end production ML systems at scale. Experience with production LLM-scale systems is a significant advantage.
• Have experience incorporating human feedback to enhance LLM-based systems using techniques such as DPO, KTO, and reinforcement fine-tuning.
• Skilled in designing end-to-end technical specifications and modular architectures for ML frameworks in complex problem domains, in partnership with product teams.
• Proficient with large-scale, distributed data processing frameworks/tools (e.g., Apache Beam, Apache Spark) and cloud platforms (e.g., GCP, AWS).

Where You'll Be

• We offer the flexibility to work where you are most effective, within the North American region, provided we have a work location available.
• This team operates within the Eastern Standard time zone to facilitate collaboration.

Compensation and Benefits

The United States base salary range for this position is $184,050 - $262,928, plus equity. Available benefits include health insurance, six months of paid parental leave, a 401(k) retirement plan, a monthly meal allowance, 23 paid days off, 13 paid flexible holidays, and paid sick leave. Please note that these ranges may be subject to future adjustments.