Senior Machine Learning Engineer - Enrichment & Content Intelligence

Spotify
New York, US
On-site

Who this role is best for

Aimed at senior engineers who specialize in multimodal machine learning and entity resolution at production scale, particularly in audio and video content understanding.

Best fit for

  • Experienced ML engineers focused on audio and video content understanding at scale.
    — “multimodal machine learning, entity resolution, and production-scale engineering
  • Candidates with a background in metadata-resolution and content-enrichment infrastructure.
    — “metadata-resolution and content-enrichment infrastructure
  • Engineers who thrive at the intersection of ML and large-scale systems.
    — “intersection of multimodal machine learning, entity resolution, and production-scale engineering

Things to consider

  • Role involves working with global-scale content understanding systems.
    — “understand music and video content at global scale
  • Focus on foundational content questions impacting multiple Spotify products.
    — “answer foundational questions across the platform

How to stand out

  • Highlight experience with audio and video content understanding in ML systems.
    — “audio, video, and metadata understanding problems at massive scale
  • Demonstrate past work on entity resolution in production environments.
    — “entity resolution, and production-scale engineering
  • Show impact of ML systems on user-facing products.
    — “powers products and experiences used by millions of listeners
Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · CompanyLevel · Senior

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • evolving machine learning systems
  • improving metadata-resolution infrastructure
  • enhancing content-enrichment systems
  • shaping content understanding across Spotify's catalog
Typical background
machine learningdata engineeringproduction-scale engineering

Skills & requirements

Required

Machine LearningEntity ResolutionMultimodal Machine LearningProduction-scale EngineeringAudio And Video Understanding

Preferred

Metadata ResolutionContent EnrichmentRecommendation Systems

Stack & domain

PythonReactLeadershipCommunicationAWSCFAFinanceHealthcare

About the role

Original posting from Spotify via Lever

The Experience team designs 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 Enrichment & Content Intelligence team sits within Content Platform in the Experience Mission. We build the metadata-resolution and content-enrichment infrastructure that powers how Spotify understands music and video content at global scale. Our systems help answer foundational questions across the platform: which tracks are the same recording, which music videos match which audio tracks, who wrote and performed a song, and how content relationships connect across Spotify’s catalog.

Our infrastructure powers products and experiences used by millions of listeners, artists, and creators every day. From recommendations and charts to royalties and artist tooling, the work we do directly shapes how content is understood and surfaced across Spotify.

We’re looking for a Senior Machine Learning Engineer to help evolve the machine learning systems behind Recording Groups, Music Video Resolution, SongDNA, and the Music Knowledge Graph. This role sits at the intersection of multimodal machine learning, entity resolution, and production-scale engineering, with opportunities to work across audio, video, and metadata understanding problems at massive scale.

Source: Spotify careers (Lever)

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