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Staff Machine Learning Engineer - Content Intelligence

Spotify · Hybrid

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MeritLog keeps this source-backed description for reference. Availability is not verified, and there is no application link here.

Last seen by MeritLog September 1, 2026Source: LeverSource version: lever-postings-v1

Source: the employer's Lever job board. Open the original listing for current details. Availability is not verified for this retained page.

Job details

Work model
Hybrid
Salary
Not listed by source
Location
London; Stockholm
Occupation
Computer Systems Engineers/Architects(O*NET 15-1299.08)
Company website
newsroom.spotify.com

Job description

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.

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