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Research Scientist - Personalization

at Spotify

Back to all Data Science / AI / ML jobs
Spotify logo
Industry not specified

Research Scientist - Personalization

at Spotify

JuniorNo visa sponsorshipData Science/AI/ML

Posted 12 minutes ago

No clicks

Compensation
$133,194 – $190,278 USD

Currency: $ (USD)

City
New York City, Boston
Country
United States

**Research Scientist - Personalization** Drive Spotify’s Personalization team, creating tailored experiences for millions. Craft original research in machine learning and AI, focusing on large-scale foundation models and generative AI. Develop novel methodologies and models to advance personalized listening. Ideal candidate needs a PhD in relevant field, 5+ years of experience, proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch), and strong Python skills. Embrace a test-driven culture and collaborate cross-functionally to shape Spotify’s products.

Department: Data and Analytics

Team: Personalization

Location: New York, NY, Boston, MA

Type: Permanent

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.
     

    Research Scientist - Personalization

    at Spotify

    Back to all Data Science / AI / ML jobs
    Spotify logo
    Industry not specified

    Research Scientist - Personalization

    at Spotify

    JuniorNo visa sponsorshipData Science/AI/ML

    Posted 12 minutes ago

    No clicks

    Compensation
    $133,194 – $190,278 USD

    Currency: $ (USD)

    City
    New York City, Boston
    Country
    United States

    **Research Scientist - Personalization** Drive Spotify’s Personalization team, creating tailored experiences for millions. Craft original research in machine learning and AI, focusing on large-scale foundation models and generative AI. Develop novel methodologies and models to advance personalized listening. Ideal candidate needs a PhD in relevant field, 5+ years of experience, proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch), and strong Python skills. Embrace a test-driven culture and collaborate cross-functionally to shape Spotify’s products.

    Department: Data and Analytics

    Team: Personalization

    Location: New York, NY, Boston, MA

    Type: Permanent

    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.
     

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