Senior Staff Machine Learning Engineer - Content Platform
Spotify · New York, NY
- Location
- New York, NY
- Level
- Staff
- Posted
- 4 months ago
About this role
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 Senior Staff Machine Learning Engineer to build and scale foundational ML systems that power content understanding, safety, and decisioning across the platform. In this role, you’ll shape the architecture and technical strategy that ensures content is evaluated, governed, and safely delivered at global scale. This work is foundational to delivering safe, high-quality experiences for both listeners and creators, while enabling new ways to interact with content across Spotify.
What You Will Do
Shape the machine learning strategy for content understanding and platform-level decisioning
Build & scale ML systems for classification, moderation, ranking, risk detection across multimodal content
Develop automated decisioning systems that ensure content quality, integrity, & policy compliance at scale
Design and deploy models across text, audio, image, and video domains
Build systems that enable controlled, reliable access to content and metadata for downstream applications
Collaborate with product, policy, trust & safety teams to operationalize content standards across platform
Improve automation to reduce manual intervention while maintaining high standards of trust and quality
Mentor engineers and contribute to best practices in ML engineering, evaluation, and system design
Who You Are
You have strong experience building production-grade machine learning systems at scale
You are experienced with modern ML frameworks such as PyTorch, TensorFlow, or JAX
You have worked with or are interested in multimodal machine learning
You understand how to design systems that balance automation with quality, safety, and user experience
You are comfortable working on complex, ambiguous problems with high impact
You think in systems, connecting models to platform-level outcomes and user experiences
You care deeply about data quality, evaluation rigor, and system reliability
You communicate clearly and influence across technical and non-technical teams
Where You Will Be
This role is based in London or Stockholm
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.
As published by Spotify. Applications are handled on their site.
One click, then it is written
Apply to Spotify with a resume written for this role.
Queue Senior Staff Machine Learning Engineer - Content Platform and I read the posting, rewrite your resume against it, draft the cover letter, and score the fit. Then you press send, or press one button and I fill in Spotify’s form for you.
01Drop your resume
A PDF or a LinkedIn URL. About a minute, once.
02I rank the openings
Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.
03Each one is written up
Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.
- 25 sent a week, free
- No card
- Nothing sent until you say so
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Put this to work
Paste your career in once. Every application after that is written for you.
Drop a resume or a LinkedIn URL. I rank the live openings against it, rewrite the resume and write a cover letter for the best of them, and fill in the employer's form when you press the button. You read, you decide what goes out.
01Drop your resume
A PDF or a LinkedIn URL. About a minute, once.
02I rank the openings
Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.
03Each one is written up
Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.
- New matches ranked and written before you are up.
- Every bullet stays inside what your history supports. Nothing invented.
- Queued, submitted, interviewing, offer: one screen, not a spreadsheet.
500 free credits on sign-up. No card. Nothing is sent until you say so.
Listed from the job board Spotify publishes. Refolk is not the employer and does not handle their hiring. Applications go to Spotify directly.