Audio Machine Learning Jobs (NOW HIRING)

Description
Research Scholar ( Part-time)
New York University Tandon School of Engineering
The Music and Audio Research Lab (MARL) at NYU is seeking to hire a Part Time Research Scholar to work with Dr. Magdalena Fuentes on research in audio and music artificial intelligence, with a particular focus on large audio language models, multimodal learning, and their applications to music and sound.
New York University (NYU) is one of the top private universities in the United States, and the Tandon School of Engineering, located in Brooklyn, NY, is deeply committed to excellence in teaching and learning. Tandon fosters student and faculty innovation and entrepreneurship that make a difference in the world. MARL conducts interdisciplinary research at the intersection of music, audio, machine learning, and human-centered technology.
This project focuses on developing and studying large audio language models (LALMs) and related multimodal AI systems for applications in music and sound. The research will investigate how these models understand, reason about, and interact with audio, as well as how their behavior can be evaluated, interpreted, and improved. Potential applications include music understanding and production, audio captioning, audio-language interaction, and intelligent tools for working with audio.
Responsibilities
The Part Time Research Scholar will support research on large audio language models and related AI systems for music and sound. Responsibilities may include:

• Developing, curating, and organizing audio, music, and audio-language datasets.
• Running and evaluating audio large language models and related multimodal models.
• Designing experiments to study model capabilities, limitations, robustness, and reasoning behavior.
• Investigating model behavior through interpretability, explainability, or mechanistic analysis methods.
• Developing benchmarks, evaluation metrics, and analysis tools for audio-language models.
• Building data processing, annotation, and experimental pipelines.
• Maintaining clear documentation, file organization, and reproducible code for the dataset pipeline.
• Contributing to open source projects.
• Attending regular meetings with the supervising faculty.
• Participating in MARL group meetings and the broader research community.

The Research Scholar A will meet regularly with the supervising faculty to discuss progress, set goals, and receive feedback. The Research Scholar A based on progress toward agreed-upon research goals, quality and organization of research outputs, datasets, and experimental work, reliability of code and documentation, ability to communicate progress clearly, responsiveness to feedback, and professional growth in research, software development, data stewardship, and collaboration.
Salary range
In compliance with NYC's Pay Transparency Act, the hourly rate for this position is $40/hour, depending on the candidate's experience and qualifications.
Expected start date and period of employment
Expected start date is: September 16, 2026. This position is expected to continue through June 15, 2027. Part time appointments would require a work schedule of approximately 27 hours per week.
Work may be conducted both in person and remotely, with regular meetings held in person.
Qualifications
Candidates should hold a Masters degree in Music Technology, Computer Science, Integrated Design & Media, Electrical and Computer Engineering, or a related field. Candidates will be required to present eligibility to work in the United States.
The successful candidate should have familiarity with Python programming, audio processing, and machine learning. Experience with audio or music AI, large audio language models, multimodal learning, deep learning frameworks, or audio research is desirable. Experience with tools such as PyTorch, librosa, torchaudio, soundfile, Hugging Face, Git/GitHub workflows, dataset annotation, or machine learning experimentation is preferred but not required.
Application Instructions
Applicants should submit the following information:

• Resume
• Names and contact information for two references.

Review of applications will begin as soon as possible and will continue until the position is filled.
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