Research Scientist, AI Music

Role overview Research and build machine-learning capabilities that let people generate, remix, transform, and interact with music. This applied research role connects generative audio and music understanding with usable creative products, working across technical and musical disciplines. It also calls for careful attention to rights, consent, and responsible use of music in model development.

Responsibilities - Design and develop models for music generation, transformation, remixing, and interactive creative use. - Investigate advances in generative audio, music understanding, audio representations, and related machine-learning methods. - Turn research ideas into prototypes and product-ready capabilities with engineering and music technology partners. - Create experiments and evaluation approaches for sound quality, musicality, controllability, performance, and creative usefulness. - Work with musicians, producers, and other collaborators to understand creative workflows and shape intuitive tools. - Account for data provenance, rights, artist consent, and attribution throughout model development.

Requirements - Advanced study in computer science, machine learning, audio signal processing, music technology, or a related area, or equivalent practical experience. - Strong grounding in machine learning, deep learning, and statistics, with experience building and evaluating models. - Experience in audio or music machine learning, such as generative audio, music understanding, source separation, or signal processing. - Python proficiency and experience with a modern machine-learning framework such as PyTorch. - Familiarity with audio-processing tools, datasets, and evaluation methods. - Ability to conduct independent applied research, build working prototypes, and communicate across technical and creative teams; interest in music and creative tools.

Nice to have Experience with generative audio architectures, codecs, neural vocoders, audio tokenization, text-audio or multimodal models; production or low-latency systems; music software and production workflows; subjective evaluation; responsible music-data practices; or research publications in related fields.

Benefits and work setup The listing describes scope to influence research and product direction, collaboration with researchers, engineers, music technologists, and producers, opportunities for continued learning, and competitive compensation and benefits.