Description:

The Personalization team at Spotify focuses on enhancing user experience by making music and podcast recommendations easier and more enjoyable.
The team is responsible for popular features like Discover Weekly and AI DJ, leveraging deep understanding of music and podcasts.
In this role, you will develop the engine behind the AI Playlist feature and work on improving and expanding the technology.
You will contribute to the design, development, evaluation, and maintenance of the AI Playlist engine.
Staying updated on the latest in Large Language Model (LLM) technology and applying it to the team's challenges is essential.
The role involves broad contributions to the team, including developing tooling and participating in on-call duties.
Hands-on expertise in implementing end-to-end production machine learning systems at scale using Java, Scala, Python, or similar languages is required.
Experience with frameworks such as Pytorch, TensorFlow, and Scikit-learn is considered a strong plus.

Requirements:

A strong background in Machine Learning, particularly with Large Language Models, is necessary.
Hands-on experience with Python, Flyte, and PyTorch is required.
The candidate should be comfortable transitioning quickly from idea to prototype to production.
A product-minded approach is essential, with a dedication to creating the best possible product for users.
The ideal candidate should have T-shaped skills in either Backend or Data Engineering, or preferably both.

The position offers flexibility to work from anywhere within the North America region.
The team operates within the Eastern Standard time zone for collaboration.
The United States base salary range for this position is $138,250 to $197,500, plus equity.
Benefits include health insurance, six months of paid parental leave, a 401(k) retirement plan, and a monthly meal allowance.
Employees receive 23 paid days off and 13 paid flexible holidays, along with paid sick leave.