Senior Machine Learning Engineer - Artist-First AI Music Lab

Role overview

Responsibilities

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

Basic qualifications

• 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

• check_circle The United States base range for this position is $184,049 - $262,928.00 plus equity.
• check_circle The benefits available for this position include 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.
• check_circle This range encompasses multiple levels.
• check_circle Leveling is determined during the interview process.
• check_circle Placement in a level depends on relevant work history and interview performance.
• check_circle These ranges may be modified in the future.

About the company