Spotify is seeking to pioneer and advance state-of-the-art generative technologies for music to create breakthrough experiences for fans and artists, inventing entirely new listening experiences that center and celebrate artists and creatives, while ensuring fair compensation and new revenue streams for rightsholders, artists, and songwriters.
Requirements
- 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, PyTorch, NumPy.
Responsibilities
- Conduct ground breaking research in music generation (diffusion, flow matching, or autoregressive models), 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 infrastructure and an audience of more than 700 million monthly active users.
- Create practical applications that harness generative technologies, pushing the boundaries of what’s possible in listening experiences.
- Collaborate as part of a 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.
Other
- You have a Ph.D. degree in Computer Science, Mathematics, Engineering, or a related field.
- Previous industry experience is helpful.
- 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 turning 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.
