AI Music Research Intern

This is a fully remote position, open to applicants in United States.

📋 Description

• Conduct research and experimentation with machine learning techniques for music generation, transformation, remixing, and audio comprehension.

• Utilize Python along with contemporary machine learning frameworks to create, assess, and enhance AI models and audio processing methods.

• Design experimental tools and prototypes aimed at delivering interactive, expressive, and accessible music experiences.

• Manage audio datasets, execute experiments, and analyze model performance, audio quality, and musicality.

• Collaborate with engineers, music technologists, and producers to explore creative applications.

• Document research efforts and contribute to the development of responsible AI practices.

⛳️ Requirements

• Currently enrolled in a Bachelor’s, Master’s, or PhD program in Computer Science, Machine Learning, Audio Signal Processing, Music Technology, Electrical Engineering, or a related discipline.

• Basic understanding of machine learning, deep learning, and statistical methodologies.

• Proficient in Python and knowledgeable about machine learning frameworks such as PyTorch.

• Passion for audio, music, generative AI, or innovative uses of machine learning.

• Experience with audio processing, digital signal processing, or music-related datasets through academic coursework, research, or personal projects.

• Strong analytical and problem-solving abilities, alongside a curiosity and eagerness to explore novel ideas.

• Capable of independently handling technical tasks while effectively collaborating within a multidisciplinary team.

• Genuine enthusiasm for music, creative tools, and the potential of technology to enhance musical expression.

• Involvement in academic projects, research, or personal initiatives related to 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 other tools for audio analysis and manipulation.

• Knowledge of audio embeddings, neural audio codecs, text-audio models, or multimodal learning.

• Proficient in music production software, digital audio workstations (DAWs), audio plugins, or creative coding tools.

• Background in collaborating with musicians, producers, or other creative professionals.

• Awareness of 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 creation.

• Contributions to research projects, open-source software, machine learning competitions, or relevant technical communities.

🏝️ Benefits

• Practical experience in researching and developing AI-driven music tools.

• Opportunity to tackle real-world challenges in generative AI, audio modeling, and music technology.

• Close collaboration with researchers, engineers, music technologists, and producers.

• Chance to experiment with cutting-edge technologies and share ideas for product development.

• Exposure to transforming research prototypes into effective creative tools.

• Mentorship and support for ongoing technical development and career advancement.

• Opportunity to influence the future of music discovery, creation, and expression in a responsible and creative setting.