AI Music Research Intern

Hook

. Research and experiment with machine learning approaches for music generation, transformation, remixing, and audio understanding .

Posted 11/11/2026internshipRemote • United StatesEntry LevelWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in machine learning and audio processing, with proficiency in Python and frameworks like PyTorch. Capable of developing innovative tools for music generation and transformation while collaborating effectively in multidisciplinary teams.

Highest-signal resume keywords

Machine LearningAudio ProcessingPython ProgrammingPyTorch FrameworkGenerative Audio Models

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningDeep LearningStatistical MethodsAudio Signal ProcessingMusic TechnologyAudio DatasetsGenerative AINeural Audio ArchitecturesAudio LibrariesCreative Coding

Soft Skills

Analytical SkillsProblem-SolvingCuriosityCollaborationIndependence

Tools & Technologies

LibrosaTorchaudioDigital Audio WorkstationsAudio PluginsCreative Tools

Industry Keywords

Music GenerationAudio UnderstandingResponsible AIEthical Dataset DevelopmentMusic Rights

Tech Stack

Tools & technologies

PythonPyTorch

About the role

Key responsibilities & impact

Research and experiment with machine learning approaches for music generation, transformation, remixing, and audio understanding
Use Python and modern machine learning frameworks to build, test, and evaluate AI models and audio processing techniques
Develop experimental tools and prototypes for interactive, expressive, and accessible music experiences
Process audio datasets, run experiments, and evaluate model performance, audio quality, and musicality
Collaborate with engineers, music technologists, and producers on creative use cases
Document experiments and contribute to responsible AI development

Requirements

What you’ll need

Currently pursuing a Bachelor’s, Master’s, or PhD degree in Computer Science, Machine Learning, Audio Signal Processing, Music Technology, Electrical Engineering, or a related field
Foundational knowledge of machine learning, deep learning, and statistical methods
Proficiency in Python and familiarity with machine learning frameworks such as PyTorch
Interest in audio, music, generative AI, or creative applications of machine learning
Familiarity with audio processing, digital signal processing, or music-related datasets through coursework, research, or personal projects
Strong analytical and problem-solving skills, with curiosity and willingness to experiment with new ideas
Ability to work independently on technical tasks while collaborating effectively with a multidisciplinary team
Genuine interest in music, creative tools, and how technology can expand musical expression
Academic projects, research experience, or personal projects involving audio processing, music generation, or machine learning
Familiarity with generative audio models, including diffusion-based, autoregressive, or other neural audio architectures
Experience with audio libraries such as librosa or torchaudio, or tools for audio analysis and manipulation
Familiarity with audio embeddings, neural audio codecs, text-audio models, or multimodal learning
Experience with music production software, digital audio workstations (DAWs), audio plugins, or creative coding tools
Experience collaborating with musicians, producers, or other creative professionals
Familiarity with evaluating generative models or assessing subjective qualities such as musicality, expressiveness, and controllability
Interest in responsible AI practices, including artist consent, music rights, and ethical dataset development
Contributions to research projects, open-source software, machine learning competitions, or relevant technical communities

Benefits

Comp & perks

Hands-on experience researching and building AI-powered music tools
Opportunity to work on real-world challenges in generative AI, audio modeling, and music technology
Close collaboration with researchers, engineers, music technologists, and producers
Opportunity to experiment with emerging technologies and contribute ideas to product development
Exposure to turning research prototypes into practical creative tools
Mentorship and support for continued technical learning and professional growth
Chance to help shape the future of music discovery, creation, and expression in a responsible, creative environment