Synced from Lever · 102d ago

Machine Learning Engineer

SpotifyNew York, NYPosted May 5, 2026
Machine Learning EngineerHybridStaff
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Mirrored from Spotify's own Lever careers system · refreshed hourly

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102d ago
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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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What applying to Spotify usually looks like

Based on publicly available information, candidates applying through lever for Spotify can generally expect a process consistent with common lever-based hiring workflows. This typically begins with an online application and resume submission, followed by an initial review from a recruiter or talent partner. If shortlisted, candidates may be invited to a phone or video screening to discuss background, motivation, and role fit. The process may include multiple stages such as hiring manager conversations, skills-based assessments, or panel discussions relevant to the specific role type. Response times vary depending on team needs and volume of applicants. Communication is often handled through automated updates within the lever platform, though candidates should not assume a fixed timeline. Overall, applicants can commonly expect a structured but variable experience shaped by the specific department and role.

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Machine Learning Engineer
Spotify · New York, NY
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