Note: The job is a remote job and is open to candidates in USA. Spotify is a leading music streaming service that aims to enhance the experiences of music creators and fans. They are seeking a Machine Learning Engineer to design and build AI-driven music experiences, focusing on generative AI products that prioritize artists and their connections with fans.

Responsibilities

• Design, build, evaluate, and improve machine learning training and inference pipelines that power new AI-driven music experiences and help take them to fully scaled production-ready features
• Apply machine learning and prompt engineering knowledge across complex ML pipelines to support rich user experiences involving large language models
• Create evaluation frameworks, including LLM-as-judge pipelines, to measure quality and build fast feedback loops that enable rapid and confident iteration
• Partner with music subject-matter experts to bootstrap training and reference data, including synthetic generation, expert curation, and taxonomy design
• Build scalable systems that balance experimentation velocity with production rigor, ensuring strong performance, reliability, and latency at Spotify scale
• Collaborate closely with Data Science teams to connect evaluation frameworks with real-world usage signals and continuously improve model quality
• Contribute to technical direction and engineering best practices across model deployment, observability, experimentation, and production infrastructure
• Work cross-functionally with engineering, product, design, and music industry partners to shape entirely new listening experiences for artists and fans

Skills

• Experienced in applying machine learning in production environments
• You have hands-on experience working with large language models, prompt engineering, evaluation systems, and shipping LLM-driven features in production
• You have experience building and maintaining production ML systems using Python, Java, Scala, or similar languages
• You are experienced in building large-scale data pipelines for sourcing, preparing, and evaluating training data
• You have worked with cloud platforms such as GCP, AWS, Azure, or similar infrastructure environments
• You are comfortable explaining machine learning concepts, assumptions, and trade-offs to both technical and non-technical audiences
• You have experience building user-facing products and strong judgment around conversational AI and generative user experiences
• You care deeply about experimentation, iteration, and using data to guide product and engineering decisions
• You thrive in collaborative, cross-functional teams that move quickly, experiment often, and continuously learn

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

Company Overview

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