Machine Learning Engineer

Machine Learning Engineer – Personalization

The Personalization (PZN) team 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 and keep the world listening. Hundreds of millions of people worldwide use the products we build, from destinations like Home and Search to original playlists such as Made For You, Discover Weekly and Daily Mix. The Context team’s mission is to own and innovate on contextual storytelling to enhance the listening experience. Using a mixture of human‑written content and LLMs, we strive to provide depth and connection for all listeners, unlocking community knowledge in a new way.

What You'll Do

Design, build, evaluate, and ship LLM‑based solutions that tell stories about our content and our users.

Collaborate with cross‑functional teams spanning user research, design, data science, product management, and engineering to build new product features that advance our mission to connect artists and fans in personalized and useful ways.

Prototype new approaches and productionize solutions at scale for our hundreds of millions of active users.

Promote and role‑model best practices of ML systems development, testing, evaluation, etc., both inside the team and throughout the organization.

Be part of an active group of machine‑learning practitioners.

Who You Are

An experienced ML practitioner motivated to work on complex real‑world problems in a fast‑paced and collaborative environment.

Strong background in machine learning, natural language processing, and generative AI, with experience applying theory to develop real‑world applications.

Hands‑on expertise with implementing end‑to‑end production ML systems at scale; experience with production LLM‑scale based systems is a plus.

Experience incorporating human feedback to improve LLM‑based systems using techniques such as DPO, KTO, and reinforcement fine‑tuning.

Experience designing end‑to‑end tech specs and modular architectures for ML frameworks in complex problem spaces in collaboration with product teams.

Experience with large‑scale, distributed data processing frameworks / tools like Apache Beam, Apache Spark, and cloud platforms such as GCP or AWS.

Where You'll Be

Flexible work location within North America; you can work wherever you work best as long as we have a work location.

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‑month paid parental leave, a 401(k) retirement plan, monthly meal allowance, 23 paid days off, 13 paid flexible holidays, and paid sick leave.

Spotify is an equal‑opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward‑thinking. Bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens.

At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know – we’re here to support you in any way we can.

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