Staff Machine Learning Engineer, Personalization

Job summary

Responsibilities

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. We built them by understanding the world of music and podcasts better than anyone else.

• 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.

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.

Tech stack

• Python
• PyTorch
• Ray
• Airflow
• BigQuery