The opportunity
The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Blend to Discover Weekly, we're behind some of Spotify's most-loved features.
What you'll do
Own and improve the machine learning models and systems that power the Home: feed, including the Shortcuts experience.
Design, build, and ship personalized recommendations that serve millions of Spotify listeners globally.
Build content recommendation systems for emerging agentic and AI-powered user experiences.
Train, fine-tune, evaluate, and optimize large language models using: techniques such as supervised fine-tuning (SFT), distillation, and parameter-efficient training approaches.
Partner closely with product managers, engineers, data scientists, and: designers to define and execute experimentation strategies.
Drive A/B testing, monitoring, model evaluation, and continuous optimization: of recommendation quality, reliability, and cost efficiency.
What they're looking for
- You have 8+ years of experience building and deploying machine learning systems in production environments.
- You have deep expertise in recommendation systems, ranking models,: personalization, or large-scale content discovery platforms.
- You have strong proficiency in Python and hands-on experience building machine learning systems with PyTorch.
- You are experienced with large language model training, fine-tuning,: evaluation, and optimization techniques including SFT, distillation, and LoRA.
- You have worked with large-scale inference systems and understand the: challenges of latency, reliability, and cost optimization.
- You care deeply about creating high-quality user experiences through: thoughtful application of machine learning.
- You communicate effectively across technical and non-technical audiences, and: you influence technical decisions beyond your immediate team
- You know how to design, execute, and interpret online experiments and A/B tests to improve user outcomes.
