Research Scientist, AI Music

Responsibilities

• Design and develop machine learning models for music generation, transformation and remixing
• Investigate generative audio, music understanding and audio representation learning
• Turn research prototypes into practical, high-quality AI capabilities with engineering teams
• Design experiments and evaluation frameworks for audio quality, musicality and controllability
• Work with producers and musicians to develop intuitive, musically meaningful tools
• Consider music rights, training data provenance, artist consent and attribution

Requirements

• PhD or MS in Computer Science, Machine Learning, Audio Signal Processing or related field, or equivalent experience
• Strong foundation in machine learning, deep learning and statistical methods
• Experience with audio or music machine learning, such as generative audio or source separation
• Proficiency in Python and modern ML frameworks such as PyTorch
• Familiarity with audio processing libraries, datasets and evaluation techniques
• Ability to conduct independent applied research and build working prototypes
• Strong collaboration and communication skills across technical and creative disciplines

Preferred Qualifications

• Experience training or deploying generative audio or music models
• Experience with audio codecs, neural vocoders or text-audio models
• Familiarity with music production workflows, DAWs or audio plugins
• Experience designing evaluation methods for musicality and expressiveness
• Knowledge of responsible AI practices for music, including rights-aware datasets
• Research publications in machine learning, audio processing or music information retrieval

About the Company

• Hook is a social music platform building music discovery, fan expression and creator growth tools, partnering directly with artists and rightsholders.