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# Machine Learning Engineer

- **Company:** Spotify
- **Location:** New York, NY, United States (Remote available)
- **Experience:** Expert
- **Salary:** $184,050.0
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Distributed Computing Environment, Machine Learning, Natural Language Processing, Large Language Models, Apache Spark, Generative AI, Machine Learning Operations, Apache Beam
- **Published:** September 4, 2026
- **Apply:** https://startup.jobs/senior-machine-learning-engineer-personalization-muse-spotify-7951916

## About the Role

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

## Description

* 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


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