---
title: 'Senior Machine Learning Engineer - Artist-First AI Music Lab at Spotify'
canonical: 'https://feeny.ai/job/senior-machine-learning-engineer-artist-first-ai-music-lab-spotify-new-york-3878mpf4eh5h'
type: 'job'
last_seen: '2026-09-07'
---

# Senior Machine Learning Engineer - Artist-First AI Music Lab at Spotify

- **Company:** Spotify
- **Location:** New York, NY
- **Work type:** remote
- **Posted:** 2026-09-01
- **Last confirmed live:** 2026-09-07
- **Apply:** https://jobs.lever.co/spotify/0d82639f-54c4-4e44-984e-4c9de7e8fffe

## Job description

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.

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

## About Spotify

## Company Overview
- **One-liner**: Spotify is the world's most popular audio streaming subscription service, connecting users to over 100 million tracks, 7 million podcast titles, and 700,000 audiobooks across 184 markets.
- **Entity Type**: Public (NYSE: SPOT)
- **Headquarters**: Stockholm, Sweden
- **Founded**: 2006
- **Founders**: Daniel Ek and Martin Lorentzon

## Core Business
- Primary industry: Audio streaming and digital media
- Target customers: B2C (consumers via Free and Premium tiers) and B2B (advertisers, artists, and labels through Spotify Advertising and Spotify for Artists)
- Mission: "To deliver creativity to the world—one note, one voice, one idea at a time."

## Products & Services
- **Spotify Free**: Ad-supported streaming of music, podcasts, and audiobooks
- **Spotify Premium**: Subscription tier with offline mode, improved sound quality, and ad-free listening
- **Spotify for Artists**: Analytics, promotion, and monetization tools for creators
- **Spotify Advertising**: Programmatic and self-serve ad platform for brands
- **Audiobooks**: Catalog of 700,000+ audiobook titles (market entry in 2022)

## Market Standing
- **Valuation/Market Cap**: Not disclosed in available sources; stock price reported at USD 391.23 (as of 2024-10-29)
- **Key Metric**: Annual Revenue EUR 17.2B; 777 million monthly users including 300 million subscribers (per Spotify Newsroom). Note: LinkedIn company data lists 365M users/165M subscribers — conflicting reports, likely reflecting an older snapshot.
- **Notable Investors/Partners**: Series A of USD 21.6M with 5 investors (2008); debt financing of USD 1.0B (2016); convertible notes in 2016 and 2021. Key acquisitions include Sonantic (2022), Mediachain (2017), and Tunigo (2013).
- **Growth Signals**: Headcount grew +14.2% YoY to 8,921 employees; 9 offices across 4 countries; expansion into audiobooks; 300M+ paying subscribers.

## Competitive Advantages
- Scale: largest audio streaming subscriber base globally
- Data and AI personalization: mature recommendation engines and AI-driven discovery
- Multi-format audio ecosystem: music, podcasts, and audiobooks in a single app
- Strong brand recognition and deep creator relationships

## Strategic Focus
- AI-powered personalization and generative audio tools
- Audiobook market expansion
- Podcast ecosystem growth
- Creator monetization and artist tools

## Why Work Here
- Employer rating 4.0/5.0 from 2,155 reviews (Work-Life: 4.2, Compensation: 3.9, Culture: 4.0, Career: 3.5)
- **Work

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