Research Scientist - Personalization

Spotify; United States; Hybrid; USD 133,000 - 190,000; Full time

Benefits offered by this job

Health insurance

Six month paid parental leave

401(k) retirement plan

Meal allowance

23 paid days off

13 paid flexible holidays

Job summary

Spotify is seeking a research-focused professional to advance personalization through ML/AI, including large-scale foundation models and generative AI. You will design experiments, develop models, and publish findings while collaborating with cross-functional teams to shape product opportunities.

The role emphasizes a strong research track record, collaboration, and mentorship within a team pushing the boundaries of music and talk recommendations.

Qualifications

• Master’s or PhD in machine learning, AI, or related field, or equivalent research experience.
• 2+ years of research experience in ML/AI, ideally in industry or academia.
• Track record of publications or contributions to top-tier conferences (NeurIPS, ICML, ICLR).
• Deep knowledge of ML areas such as recommender systems, generative models, or representation learning.
• Experience designing experiments and working with real-world datasets to validate ideas.
• Interest in understanding user behavior and improving experiences across music and talk content.
• Curiosity, creativity, and a collaborative problem-solving mindset.
• Value diverse perspectives and teamwork.

Responsibilities

• Conduct original research in ML/AI focusing on large-scale foundation models and generative AI.
• Develop novel methodologies, models, and evaluation frameworks for personalization systems.
• Design and execute rigorous experiments to test ideas and hypotheses.
• Publish and present findings at conferences and in publications.
• Collaborate with cross-functional teams to translate research into product opportunities.
• Help shape a forward-looking research agenda aligned with Spotify’s personalization strategy.
• Mentor teammates and foster a curious, collaborative research culture.

Skills

Machine Learning

Research

Publications

Recommender Systems

Generative AI

Python

PyTorch

Experiment Design

Education

Master's degree or PhD in ML/AI

Tools

Python

PyTorch

TensorFlow

Job description

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 $133,194 - $190,278 plus equity. The benefits available for this position include health insurance, six month paid parental leave, 401(k) retirement plan, a monthly meal allowance, 23 paid days off, 13 paid flexible holidays. 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.