Conduct research in machine learning focusing on AI, develop models, design experiments, collaborate on product ideas, and mentor researchers.
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
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.
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