Research Scientist, AI Music

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

📋 Description

• Create and implement machine learning models for music generation, transformation, remixing, and creative engagement.

• Explore innovations in generative audio, music comprehension, audio representation learning, and related fields in machine learning.

• Convert research concepts and prototypes into actionable, top-notch AI functionalities in collaboration with engineering and music technology teams.

• Design experiments and evaluation frameworks to assess audio quality, musicality, controllability, performance, and creative applicability.

• Work alongside producers, musicians, and cross-functional teams to gain insights into creative processes and develop user-friendly, musically relevant tools.

• Take into account music rights, training data provenance, artist consent, and attribution throughout the model development process.

⛳️ Requirements

• Advanced degree (PhD or MS) in Computer Science, Machine Learning, Audio Signal Processing, Music Technology, or a related field, or equivalent practical experience.

• Solid foundation in machine learning, deep learning, and statistical techniques, with hands-on experience in developing and evaluating ML models.

• Experience in audio or music-related machine learning, including generative audio, music comprehension, audio representation learning, source separation, or signal processing.

• Proficiency in Python and contemporary ML frameworks, such as PyTorch.

• Familiarity with audio processing libraries, datasets, and evaluation methodologies.

• Capability to conduct independent applied research and convert research findings into functional prototypes and real-world applications.

• Strong collaborative and communication abilities, capable of working effectively across both technical and creative domains.

• A genuine passion for music, creative tools, and the potential of technology to enhance musical expression.

• Experience in training, fine-tuning, or deploying generative audio or music models, including diffusion-based, autoregressive, or other neural audio architectures.

• Familiarity with audio codecs, neural vocoders, audio tokenization, text-audio models, or multimodal learning.

• Understanding of agent frameworks and workflow orchestration tools for developing multi-step AI applications.

• Knowledge of music production workflows, DAWs, audio plugins, or creative software.

• Experience collaborating directly with producers, musicians, or other creative professionals to create or assess AI-driven tools.

• Experience in building low-latency, interactive audio systems or deploying ML models in production settings.

• Experience designing evaluation methods for subjective qualities such as musicality, expressiveness, controllability, and creative utility.

• Awareness of responsible AI practices for music, including rights-aware dataset development, artist consent, data provenance, and attribution.

• Research publications or contributions in the fields of machine learning, audio processing, generative AI, or music information retrieval.

🏝️ Benefits

• An opportunity to influence the future of AI-driven music creation and expression.

• The freedom to pursue ambitious research ideas and impact technical and product strategies.

• Close collaboration with a diverse team of researchers, engineers, music technologists, and producers.

• The chance to witness your research evolve into practical tools utilized in creative workflows.

• A mission-oriented environment dedicated to making music more interactive, accessible, and expressive while honoring the individuals behind it.

• Support for ongoing learning, research, and professional advancement.

• Competitive salary and benefits.