What You'll Do

Design, build, evaluate, and ship LLM-based solutions that give users more adaptive control over their listening experience
Work on prompted playlist experiences with a focus on music fulfillment and session generation
Collaborate with cross-functional partners across user research, design, data science, product, and engineering
Prototype new ML approaches and bring them into production at global scale
Build and improve systems that connect artists and fans in personalized and meaningful ways
Contribute to the development of scalable ML systems serving hundreds of millions of users
Promote best practices in ML system design, testing, evaluation, and deployment across the organization
Actively contribute to a strong community of machine learning practitioners at Spotify

Who You Are

Experienced in machine learning and enjoy solving complex real-world problems in collaborative environments
Strong background in machine learning, natural language processing, and generative AI
Comfortable applying theory to build real-world, production-ready applications
Hands-on experience building and deploying end-to-end ML systems at scale
Familiar with LLM-based systems and techniques for improving them using human feedback such as reinforcement fine-tuning, DPO, or similar approaches
Experience designing modular ML architectures and writing technical specifications in partnership with product teams
Experienced with large-scale distributed data processing tools such as Apache Beam or Apache Spark
Worked with cloud platforms like GCP or AWS