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Staff Machine Learning Engineer - Content IntelligenceUnited States Digital Space LLC • New York, New York, United States
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Staff Machine Learning Engineer - Content Intelligence

United States Digital Space LLC
  • US
    New York, New York, United States
  • US
    New York, New York, United States
Jetzt Bewerben

Über

We design the company’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 the company 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 the company.
The Content Platform team powers the full lifecycle of content across music, podcasts, audiobooks, and emerging formats at the company. 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 the company. 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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  • New York, New York, United States

Sprachkenntnisse

  • English
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