Description
Join the Personalization team at Spotify and contribute to building machine learning systems that power safety across personalization surfaces such as recommendations, search, and emerging AI experiences.
As a Machine Learning Engineer - Safety, you will design, build, and improve machine learning systems that help ensure Spotify experiences and recommendations are safe, responsible, and enjoyable. You will work closely with the Tech Research, Trust & Safety, and Content Platform teams to develop new approaches in areas like synthetic data, fairness, and responsible AI.
Key responsibilities include:
- Designing, building, and improving machine learning systems that power safety across personalization surfaces
- Contributing to the platformization of safety systems, enabling scalable and reusable solutions across teams
- Partnering with Product, Trust & Safety, and Content Platform to translate safety needs into practical technical solutions
- Working on both traditional ML models and generative AI systems, including integrating third-party and in-house foundational models
- Contributing to evaluation frameworks, including labeling strategies, ground truth creation, and model validation approaches
You will work with a talented team of engineers, researchers, and product managers to build scalable, high-impact systems that support both today's products and the next generation of AI-driven experiences.
In this role, you will have the opportunity to work on complex problems, collaborate with cross-functional teams, and make a significant impact on the safety and responsibility of Spotify's experiences.
The base range for this position is $184,050 – $262,928 USD, plus equity. Benefits include health insurance, six-month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, paid flexible holidays, and paid sick leave.