Description
The Personalization team at Spotify makes deciding what to play next on Spotify easier and more enjoyable for every listener. We seek to understand the world of music, podcasts, and audiobooks better than anyone else so that we can make great recommendations to every individual person and keep the world listening.
Our Minesweeper squad produces Human Understandable Language Knowledge to enrich music and talk content understanding. We use AI and ML techniques, including Large Language Models, to understand music, podcasts and audiobooks, building reliable, scalable systems to distribute that knowledge to Spotify internal teams, users, and creators.
We are looking for a Machine Learning Engineer to join our team and help build the future of music, podcast and audiobook listening experiences for millions of listeners at Spotify. This is a unique opportunity to help develop and shape Spotify content enrichment, and recommendations.
As a Machine Learning Engineer, you will:
- Utilize in-house and 3rd party LLMs to solve language understanding problems
- Employ techniques such as fine-tuning and RAG to improve models
- Contribute to designing, building, evaluating, shipping, and refining Spotify’s product by hands-on ML development
- Help drive optimization, testing, and tooling to improve quality of our content enrichment assets
- Collaborate with cross-functional teams of MLEs, data and backend engineers, and other stakeholders including tech research, data science, and product to develop new features and technologies
- Perform data analysis to establish baselines and inform product decisions
- Stay up-to-date on the latest machine learning algorithms and techniques
You will be part of a motivated and supportive team that values agile software processes, data-driven development, reliability, and disciplined experimentation.
If you have a strong background in machine learning, especially experience with Large Language Models, and are passionate about fostering collaborative teams, we encourage you to apply.