Build Spotify’s personalized recommendations remotely with Python and PyTorch expertise. Shape Home feed experiences serving millions of listeners globally.
As a Staff Machine Learning Engineer, you will own personalization systems across Spotify Home Surfaces. The work combines recommendation systems, ranking models, large language models, experimentation, and production-scale machine learning infrastructure. You will take models from research into production while guiding technical direction in ambiguous problem spaces.
Key Responsibilities: Own machine learning models powering Spotify’s Home feed
Design personalized recommendations for millions of listeners
Build content systems for agentic and AI-powered experiences
Drive experimentation, monitoring, evaluation, and optimization
Improve platforms,
pipelines, and production personalization systems
Requirements: Eight or more years building production machine learning systems
Deep expertise in recommendations, ranking, personalization, or discovery
Solid Python proficiency and hands-on PyTorch experience
Experience training, fine-tuning, evaluating, and optimizing large language models
Understanding of large-scale inference latency, reliability, and cost
Apply recommendation systems, Python, PyTorch, and machine learning leadership to Spotify’s globally scaled Home experiences remotely.