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# Senior Machine Learning Engineer (Enrichment & Content Intelligence)

- **Company:** Spotify
- **Location:** New York, NY, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Airflow, Computer Vision, BigQuery, Data Deduplication, Distributed Computing Environment, Data Flow Control, Graph Database, Machine Learning, Recommender Systems, Tensorflow, Web Application Frameworks, Pytorch, Machine Learning Operations, Entity Resolution
- **Published:** November 8, 2026
- **Apply:** https://www.juju.com/job/28_25303_36bb4442d21141f46f49286cbbdf36bd

## About the Role

* 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.

## Description

* 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., * You have solid experience building, deploying, and maintaining machine learning systems in production at scale.