About the role

What will you do at Spotify?

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. Join us and you’ll keep millions of

users listening by making great recommendations to each and every one of them.

Spotify’s Personalization organization builds the technology that helps millions

of listeners discover what they love. Within this space, our research team

focuses on advancing the state of the art in machine learning and AI to shape

the future of personalization. We explore new approaches, challenge existing

assumptions, and contribute to the broader research community while influencing

long-term product direction.

What You'll Do

* Conduct original research in machine learning and artificial intelligence,
with a focus on large-scale foundation models and generative AI
* Develop novel methodologies, models, and evaluation frameworks to advance
personalization systems
* Design and execute rigorous experiments to explore new ideas and validate
research hypotheses
* Contribute to the scientific community through publications, talks, and
conference participation
* Collaborate with cross-functional partners to translate research insights
into long-term product opportunities
* Help define and evolve a forward-looking research agenda aligned with
Spotify’s personalization strategy
* Mentor others and contribute to a strong, curious, and collaborative research
culture

Who You Are

* You have a Master’s or PhD in machine learning, artificial intelligence, or a
related field, or equivalent research experience
* You have 2+ years of experience conducting research in machine learning or
AI, ideally in an industry or academic setting
* You have a track record of publications or contributions to top-tier
conferences such as NeurIPS, ICML, ICLR, or similar
* You have deep knowledge of machine learning, with experience in areas such as
recommender systems, generative models, or representation learning
* You are experienced in designing experiments and working with real-world
datasets to validate research ideas
* You care about advancing understanding of user behavior and improving
experiences across music and talk content
* You bring curiosity, creativity, and a thoughtful approach to solving
complex, open-ended problems
* You value collaboration and actively seek diverse perspectives in your work
Where You'll Be
* This role is based in New York City or Boston
* We offer you the flexibility to work where you work best! There will be some
in person meetings, but still allows for flexibility to work from home
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The United States base range for this position is $169,157–$241,653 USD, plus
equity. The benefits available for this position 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. These ranges may
be modified in the future.
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! So 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.

Which skills does this role require?

Machine learningArtificial intelligenceLarge-scale foundation modelsGenerative AIRecommender systemsRepresentation learningExperimental designData analysisResearch methodologyMentoringProduct strategyScientific communicationPersonalizationFoundation modelsNeurIPSICMLICLRResearchProduct developmentMusic streamingPodcastingMentorshipAlgorithm developmentMachine LearningLLMs

Make your next move

Build a shortlist and prepare

Identify the requirements you can demonstrate, then choose examples from your work to discuss with the hiring team.

Build a focused shortlist before you applyCompare role requirements with your experience and give each application a clear reason.
Practice explaining your experience in an interviewRehearse your answers before meeting the hiring team.

Review the responsibilities and requirements before adding an opening to your shortlist.