Machine Learning Engineer

The Personalization (PZN) team at Spotify 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.

The TurnTable team’s mission is to own and innovate on AI DJ and the interactive listening experiences. Using a mixture of LLMs and traditional ML, we strive to provide depth and connection for all listeners. We are looking for a Machine Learning Engineer to join our team to build and improve our interactive listening experiences.

Responsibilities

• Design, build, evaluate, and ship an agent-based DJ solution that brings our DJ and interactive experiences to the next level.
• 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.

Requirements

• 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. Experience with production LLM scale-based systems is a plus.
• Experience with incorporating human feedback to improve LLM-based systems using techniques like DPO, KTO, and reinforcement fine-tuning.
• Experience 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.

Benefits

• Health insurance
• Six-month paid parental leave
• 401(k) retirement plan
• Monthly meal allowance
• 23 paid days off
• 13 paid flexible holidays
• Paid sick leave

The United States base range for this position is $176,166 - $251,666 plus equity.