Backend Engineer, Music
We are looking for a Backend focused engineer to join the OASIS team. OASIS builds and operates the systems that power promotion delivery and optimization within Discovery Mode. Our work ensures that promotional content isn’t just "surfaced", but is intelligently allocated by balancing complex, competing objectives across our entire ecosystem.
The team is distributed and highly collaborative, working closely with Personalization (PZN) to serve high-quality promotion signals. You’ll be part of a small, impactful group of engineers across data and machine learning, owning a core piece of infrastructure that enables promotion delivery at scale.
Own and evolve backend systems that deliver promotion scores to personalization systems (PZN)
Build and maintain services that support promotion allocation and delivery at scale
Collaborate closely with machine learning engineers and data engineers to improve signal quality and system performance
Contribute to system design decisions that impact a critical part of Spotify’s discovery ecosystem
Improve reliability, scalability, and observability of existing infrastructure
Partner with cross-functional teams to ensure seamless integration with personalization workflows
Gradually expand your scope into adjacent areas such as data pipelines or ML-adjacent systems
You have experience building backend systems using Java or similar languages
You are comfortable working across systems and are interested in learning beyond pure backend (e.g., data or ML systems)
You are driven to leverage AI to improve our systems, and eager to find practical ways to apply it
You have experience working with or exposure to Scala, Python, or data/ML workflows
You are excited to grow into a T-shaped engineer with breadth across backend, data, and ML-adjacent domains
You care about ownership and are motivated to take responsibility for evolving critical systems
You collaborate effectively with cross-functional teams, including personalization and data partners