About the Role
The role involves developing advanced machine learning models to deepen understanding of music and user preferences, enabling more accurate and meaningful recommendations across the platform.
Responsibilities
- Design and implement scalable machine learning models for music understanding tasks
- Collaborate with data scientists and engineers to integrate models into production systems
- Analyze audio signals and metadata to extract meaningful music features
- Optimize recommendation algorithms based on user listening patterns
- Work closely with research teams to prototype and validate new ideas
- Evaluate model performance using statistical and qualitative methods
- Improve personalization by leveraging deep learning on large-scale datasets
- Develop systems that adapt to evolving user tastes over time
- Contribute to the architecture of real-time inference pipelines
- Ensure models are robust, interpretable, and aligned with user experience goals
- Participate in code reviews and maintain high engineering standards
- Troubleshoot and resolve issues in live machine learning systems
- Stay current with advancements in audio processing and recommendation systems
- Collaborate across disciplines to define success metrics for personalization
- Build tools and infrastructure to streamline model training and deployment
- Support data quality initiatives to enhance training dataset reliability
- Work with product teams to align technical capabilities with user needs
- Contribute to documentation and knowledge sharing within the team
- Mentor junior engineers and support team growth
- Drive initiatives to improve model fairness and reduce bias
- Ensure compliance with privacy standards in data handling and model design
- Optimize resource usage in distributed training environments
- Develop evaluation frameworks for A/B testing of personalization features
- Integrate third-party music data sources where applicable
- Contribute to long-term roadmap planning for music understanding systems
Compensation
Competitive salary and benefits package
Work Arrangement
Hybrid work model with flexibility based on location and team needs
Team
Part of the Personalization group focused on enhancing music discovery and user experience
Why This Role Matters
- Music is deeply personal, and how users discover new content shapes their experience. This role directly influences how millions interact with music by building systems that understand both audio and context at a deep level.
- The work contributes to making music discovery intuitive, diverse, and reflective of individual tastes across cultures and genres.
What We Look For
- We value engineers who combine technical depth with curiosity about human behavior and artistic expression.
- Candidates should demonstrate a balance between innovation and practicality, delivering solutions that scale while respecting user intent and privacy.
Available for qualified candidates requiring sponsorship
