AI Music Research Intern

Responsibilities

• Research and experiment with machine learning approaches for music generation, transformation and audio understanding
• Implement and evaluate models using Python and modern ML frameworks
• Build experimental prototypes for interactive, expressive music tools
• Process audio datasets, run experiments and evaluate model performance and musicality
• Collaborate with engineers, music technologists and producers and document findings

Requirements

• Currently pursuing a Bachelor's, Master's or PhD in Computer Science, Machine Learning, Audio Signal Processing or related field
• Foundational knowledge of machine learning, deep learning and statistical methods
• Proficiency in Python and familiarity with PyTorch
• Interest in audio, music and generative AI
• Strong analytical and problem-solving skills

Preferred Qualifications

• Audio processing or music generation projects
• Familiarity with generative audio models and audio libraries such as librosa or torchaudio
• Experience with DAWs, audio plugins or creative coding tools
• Interest in responsible AI practices, artist consent and music rights

Benefits

• Hands-on experience building AI-powered music tools
• Close collaboration with researchers, engineers and producers
• Mentorship and support for technical growth

About the Company

• Hook is a social music platform building music discovery, fan expression and creator growth tools, backed by top-tier investors.