We design Spotify’s consumer experience - end to end, moment to moment, across every screen, platform, and partner integration. Our mission is to make listening feel effortless, personal, and joyful for billions of users around the world. That means turning complexity into clarity across hundreds of touchpoints—from our mobile and desktop apps to the smart speakers, TVs, cars, and integrations where Spotify shows up every day. If it touches a consumer, we shape it. We bring deep insight into human behavior, design, and technology to craft experiences that feel intuitive, expressive, and unmistakably Spotify.
The Content Platform team powers the full lifecycle of content across music, podcasts, audiobooks, and emerging formats at Spotify. We ensure that everything from licensed catalog to user-generated content is trusted, safe, and high quality for millions of listeners worldwide. Our systems are responsible for how content is ingested, understood, enriched, governed, and distributed across the platform. As the scale and diversity of content continues to grow—driven by advances in AI and new creation tools—we’re building intelligent systems that can evaluate, manage, and route content reliably at global scale.
We’re seeking a Staff Machine Learning Engineer to build and scale foundational ML systems that power content understanding across Spotify. In this role, you’ll work on systems that generate deep, machine-readable understanding of content across audio, video, text, and images—enabling automation, improving quality, and unlocking new product experiences. This work is central to delivering safe, high-quality, and differentiated experiences for millions of listeners and creators worldwide.
What You Will Do
Build and scale machine learning systems that generate deep understanding of content across modalities
Develop models for classification, tagging, semantic understanding, and content enrichment
Create high quality content enrichment at scale using LLMs and agentic systems.
Design systems that make content intelligence signals available to downstream teams and products
Improve automation for content quality, safety, and metadata enrichment at scale
Collaborate with product, policy, and engineering teams to translate content intelligence into user impact
Contribute to evaluation frameworks, data pipelines, and annotation systems
Support rapid experimentation to prototype and launch new types of content signals
Help improve system reliability, scalability, and performance across large datasets
Who You Are
You have experience building and deploying machine learning systems in production
You are comfortable working with ML frameworks such as PyTorch, TensorFlow, or similar
You have experience working with large datasets and care about data quality and evaluation
You are interested in or have worked with multimodal machine learning
You understand how to design systems that balance automation with quality and user experience
You are comfortable working on complex problems with evolving requirements
You think in systems and understand how models connect to product outcomes
You communicate clearly and work well across technical and non-technical teams
Where You Will Be
- This role is based in New York, NY
- We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home.
Skills Required
- Experience building and deploying machine learning systems in production
- Comfort with ML frameworks such as PyTorch, TensorFlow
- Experience working with large datasets
- Interest in or experience with multimodal machine learning
Spotify Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Spotify and has not been reviewed or approved by Spotify.
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Flexible Benefits — Employees consistently praise the total compensation package beyond base salary, highlighting a mix of RSUs, cash incentives, and stipends alongside core pay. The package is described as flexible and customizable through equity choices (e.g., RSUs, options, cash) that can be tailored for long-term wealth building.
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Leave & Time Off Breadth — Time-off offerings are repeatedly highlighted as substantial, including generous vacation, paid sick days, volunteer time, and flexible holidays. These policies are framed as a meaningful part of the overall rewards experience beyond salary.
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Healthcare Strength — Health coverage is portrayed as comprehensive, spanning medical, dental, vision, life insurance, disability coverage, and mental health support. Additional employer contributions to HSAs are cited as strengthening the overall health and wellness value proposition.
Spotify Insights
What We Do
Spotify transformed music listening forever when it launched in Sweden in 2008. Discover, manage and share over 50m tracks for free, or upgrade to Spotify Premium to access exclusive features including offline mode, improved sound quality, and an ad-free music listening experience.
