1 day ago
Base Salary
$184k - $263k/yr
Responsibilities
- Own and evolve large-scale ML pipelines powering Spotify’s content-resolution systems.
- Lead development of multimodal embedding frameworks for music video matching and SongDNA.
- Improve entity-resolution systems for better understanding of content relationships.
- Design and run experiments to enhance content quality outcomes.
- Build scalable ML evaluation and monitoring infrastructure.
- Contribute to the evolution of the Music Knowledge Graph.
- Partner with Product Managers, Data Scientists, and engineering teams.
- Help shape technical strategy and contribute to long-term ML direction.
- Mentor engineers and foster a culture of collaboration and experimentation.
Requirements
- Solid experience building, deploying, and maintaining machine learning systems in production at scale.
- Strong experience with ML models using frameworks like PyTorch or TensorFlow.
- Experience with multimodal machine learning systems across audio, computer vision, or text embeddings.
- Understanding of entity resolution, deduplication, and large-scale matching problems.
- Ability to design evaluation systems balancing model quality and operational performance.
- Experience with large-scale distributed data processing systems and ML infrastructure.
- Effective communication skills across engineering, product, and data science teams.
- Comfortable leading technical initiatives and influencing engineering direction.
- Experience with Scio, Dataflow, Flyte, BigQuery, or similar frameworks is a plus.
- Experience with Scala and computer vision or recommendation systems is a strong plus.
Benefits
- Health insurance.
- Six-month paid parental leave.
- 401(k) retirement plan.
- Monthly meal allowance.
- 23 paid days off.
- Paid flexible holidays.
- Paid sick leave.