• Lead and support a team of Backend, Data, and Machine Learning Engineers building recommendation systems used by hundreds of millions of listeners • Set the technical direction for recommendation models across surfaces like Home and Now Playing • Guide the development of candidate generation, ranking, and embedding systems that improve music discovery • Partner with ML platform and infrastructure teams to evolve and scale generative recommendation models • Work closely with Product, Data Science, and Design to define success metrics and turn insights into meaningful product improvements • Ensure systems are reliable, efficient, and able to operate at global scale with low latency • Support strong engineering practices across experimentation, model evaluation, and production monitoring • Stay close to the technical work by reviewing architecture decisions and contributing to key discussions • Encourage thoughtful adoption of AI-assisted development tools to improve team productivity and reduce repetitive work • Create an inclusive, supportive team environment where engineers can grow and do their best work • Collaborate with peers across the organization to align on shared goals and technical direction