Senior Machine Learning Engineer - Artist-First AI Music Lab
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 18h ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 14d ago
The date the source published, not the day we noticed it (2026-09-01). Last seen at its source 1h ago.
Is it remote?
Marked remote on the employer's board
Their board carries a remote setting on this posting — a field they filled in, not wording we read. The location field names somewhere specific, which is usually where the team or the entity sits.
Who may apply?
United States
The description states no restriction of its own. This is the source's own tag.
Pay not stated
Similar roles pay $160.9k–210k/yr
Middle 50% of 740 listings that do state pay — Engineering · Senior · United States · USD/year. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
lever employer's own board first seen 10d ago · last seen 1h ago
The listing
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. We invent entirely new listening experiences that center and celebrate artists and creatives. All of our products will put artists and songwriters first, through these four principles:
- Partnerships with record labels, distributors, and music publishers: We’ll develop new products for artists and fans through upfront agreements, not by asking for forgiveness later.
- Choice in participation: We recognize there’s a wide range of views on use of generative music tools within the artistic community. Therefore, artists and rights-holders will choose if and how to participate to ensure the use of AI tools aligns with the values of the people behind the music.
- Fair compensation and new revenue: We will build products that create wholly new revenue streams for rightsholders, artists, and songwriters, ensuring they are properly compensated for uses of their work and transparently credited for their contributions.
- Artist-fan connection: AI tools we develop will not replace human artistry. They will give artists new ways to be creative and connect with fans. We will leverage our role as the place where more than 700 million people already come to listen to music every month to ensure that generative AI deepens artist-fan connections.
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.
- 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.
Who You Are
- 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.
Where You’ll Be
- We offer you the flexibility to work where you work best! For this role, you can be within the Eastern United States region as long as we have a work location.
- This team operates within the EST time zone for collaboration.