AI Music Research Intern

Role overview

Explore how machine learning can support music creation, transformation, remixing, and understanding. The work combines research and practical prototyping: you will investigate emerging methods, run experiments with audio data, and help shape experimental tools for creative use. The role also calls for thoughtful consideration of music rights and the people whose work and data may be involved.

Responsibilities

- Research and experiment with machine learning approaches for generative audio, music transformation, remixing, and audio understanding. - Build, test, and evaluate models and audio-processing methods using Python and modern machine learning frameworks. - Create prototypes exploring more interactive and expressive ways to work with music. - Prepare audio datasets, run experiments, and assess model performance, audio quality, and musicality. - Share and document findings with engineering, music technology, product, and creative colleagues. - Consider responsible data and rights practices while exploring potential creative applications.

Requirements

- Currently pursuing a bachelor's, master's, or doctoral 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 a machine learning framework such as PyTorch. - Familiarity with audio processing, digital signal processing, or music datasets through coursework, research, or projects. - Analytical and problem-solving ability, curiosity, and willingness to experiment. - Ability to work independently on technical tasks and collaborate with a multidisciplinary team.

Nice to have

- Projects or research in audio processing, music generation, or machine learning. - Experience with generative audio architectures, audio libraries such as librosa or torchaudio, embeddings, codecs, or text-audio models. - Familiarity with music production software, audio plugins, or creative coding, or experience working with musicians and producers. - Interest in evaluating musicality and controllability or in artist consent, music rights, and responsible dataset development.

Benefits and work setup

The internship includes practical work on AI music tools and exposure to turning research prototypes into creative applications. You will collaborate with researchers, engineers, music technologists, and producers, with mentorship and opportunities to contribute ideas to product development.