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SpotifySpotifyNew York, NY

Senior Machine Learning Engineer - Enrichment & Content Intelligence

As a Senior Machine Learning Engineer, you will evolve large-scale ML pipelines and multimodal embedding frameworks to power Spotify's content-resolution systems. You will improve entity-resolution across music and video content, design experiments, and build scalable ML evaluation and monitoring infrastructure.

Salary not listed
HybridML Engineering

About the role

What You'll Do

  • Own and evolve large-scale ML pipelines powering Spotify’s content-resolution systems
  • Lead development of multimodal embedding frameworks supporting multimodal understanding, music video matching, SongDNA
  • Improve entity-resolution systems across music and video content, helping Spotify better understand relationships between recordings, versions, and content formats
  • Design and run experiments to improve precision, recall, and overall content-quality outcomes using offline evaluation, golden datasets, A/B testing, and impact analysis
  • Build scalable ML evaluation and monitoring infrastructure, including standardized datasets, retraining workflows, and continuous improvement systems
  • Contribute to the evolution of the Music Knowledge Graph by improving production ML capabilities, observability, and model lifecycle management
  • Partner closely with Product Managers, Data Scientists, and engineering teams across Content Platform and the wider Experience Mission
  • Help shape technical strategy for the squad and contribute to long-term ML direction across the product area
  • Mentor engineers and contribute to a strong culture of technical collaboration and experimentation

Who You Are

  • You have solid experience building, deploying, and maintaining machine learning systems in production at scale
  • You have strong experience training, evaluating, and operating ML models using modern frameworks such as PyTorch or TensorFlow
  • You have experience working with multimodal machine learning systems across audio, computer vision, text embeddings, or related domains
  • You understand entity resolution, deduplication, record linkage, or large-scale matching problems, ideally across multiple content modalities
  • You know how to design evaluation systems that balance model quality, operational performance, and real-world impact
  • You are experienced working with large-scale distributed data processing systems and ML infrastructure
  • You communicate effectively across engineering, product, and data science stakeholders
  • You are comfortable leading technical initiatives and influencing engineering direction within a team
  • Experience with Scio, Dataflow, Flyte, BigQuery, or similar distributed processing frameworks is a plus
  • Experience with Scala is a plus
  • Experience with computer vision, video understanding, multimodal embeddings, or recommendation systems is a strong plus

Skills

PyTorchTensorFlowMultimodal Machine LearningEntity ResolutionDistributed Data ProcessingScioDataflowFlyteBigQueryScalaComputer VisionVideo UnderstandingRecommendation Systems

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