Data, Research & Insights

Tech Research

We are seeking a Research Scientist to help shape the future of music consumption on Spotify. Our team pioneers and advances state-of-the-art generative music technologies, enabling innovative personalization features, celebrating artists, and opening the door to entirely new possibilities. A core principle is ensuring that everyone involved—listeners, artists, and the industry—values our products and can opt out at any time. We develop features that enhance current offerings and lay the foundation for groundbreaking new products.

Location

New York

Job type

Permanent

What You'll Do

Conduct cutting-edge research in music generation, as well as related domains like ML-based audio processing, music information retrieval, machine learning, and signal processing.
Run large-scale experiments with access to Spotify’s extensive computing infrastructure, a catalog of over 100 million songs, and an audience of more than 600 million monthly active users.
Create practical applications that harness generative technologies, pushing the boundaries of what’s possible in music listening experiences.
Collaborate as part of an autonomous, cross-functional team—working closely with scientists, engineers, product managers, designers, user researchers, and analysts—to craft innovative solutions to complex challenges.
Have a direct impact on Spotify’s products, tools, and services, working on projects that influence the entire organization.
Engage with the broader research community by publishing your findings, delivering talks, and attending top conferences.

Who You Are

You have a Ph.D. degree in Computer Science, Mathematics, Engineering, or a related field. Previous industry experience is helpful.
You have experience in one or more of the following fields: generative modeling, machine learning, music information retrieval, speech processing, audio processing, signal processing, probabilistic modeling, computer vision, or related areas.
You have publications in communities such as ICASSP, ISMIR, Interspeech, ICLR, AAAI, IJCAI, NeurIPS, ICML, CVPR, ECCV, ICCV, or related.
You have strong coding skills in the following languages/libraries: Python, NumPy, PyTorch / Tensorflow.
You are a creative problem solver who is passionate about building outstanding products that add real value to millions of people.
You are enthusiastic about learning more about audio processing and music information retrieval as well as developing research ideas into products operating at scale.
You can explain complex topics in simple terms, and you enjoy building strong relationships with colleagues and stakeholders.

Where You'll Be

This role is based in New York.
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.

Our global benefits

Extensive learning opportunities, through our dedicated team, GreenHouse.

Flexible share incentives letting you choose how you share in our success.

Global parental leave, six months off - fully paid - for all new parents.

All The Feels, our employee assistance program and self-care hub.

Flexible public holidays, swap days off according to your values and beliefs.

Learn about life at Spotify

The United States base range for this position is $132,073- $188,676 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, 13 paid flexible holidays, paid sick leave. These ranges may be modified in the future.

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Spotify

Spotify, a leading music streaming service, seeks a permanent Research Scientist with a Ph.D. in relevant fields and skills in generative modeling and machine learning. The candidate will conduct research in music generation, collaborate with cross-functional teams, and impact Spotify's products. Benefits include health insurance, paid parental leave, retirement plan, meal allowance, and flexible work arrangements.

Research Scientist, Music Generation

Summary