Spotify is seeking a Research Scientist to advance state-of-the-art generative technologies for music, aiming to create breakthrough experiences for fans and artists by inventing new listening experiences that center and celebrate artists and creatives.
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.
