The opportunity
We are seeking a Senior Machine Learning Engineer to join our Artist-First AI Music lab. Our team designs and builds state-of-the-art generative products for music that create breakthrough experiences for fans and artists.
What you'll do
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.
What they're looking for
- 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.
