Audio Applied Research Science Intern

About the Role

The Signal Processing and Applied Research Science team is seeking a highly motivated Audio Applied Research Science Intern to help develop next-generation audio technologies powered by machine learning and artificial intelligence. This role offers the opportunity to contribute to cutting-edge research and product development in professional audio applications. This Internship will be Remote, Onsite or Hybrid in Niles, IL.

Responsibilities

• Conducting research and developing machine learning solutions for challenging audio problems.
• Collecting, creating, and curating datasets for model development and evaluation.
• Designing, training, and evaluating deep learning models for audio applications, including: Single- and multi-channel audio processing, Speech enhancement, Music enhancement, Audio classification, Other audio intelligence and signal processing tasks.
• Investigating and implementing state-of-the-art machine learning architectures and techniques.
• Optimizing and adapting models for deployment across a variety of hardware and software platforms.
• Applying modern machine learning engineering practices, including shared codebases, reusable toolkits, experiment tracking, and reproducible workflows.
• Documenting research findings, experimental results, and technical recommendations using collaborative documentation tools.
• Presenting technical results and insights to research and engineering teams.

Qualifications

• Currently pursuing a PhD or advanced Master's degree in Electrical Engineering, Computer Science, Mathematics, Statistics, Physics, Data Science, Machine Learning, or a related quantitative field.
• Demonstrated research or project experience in machine learning, deep learning, or artificial intelligence.
• Experience applying machine learning techniques to audio, speech, digital signal processing, multimedia, or related domains.
• Proficiency with modern machine learning frameworks and libraries such as PyTorch, TensorFlow, JAX, or equivalent.
• Strong programming skills in Python and experience working with scientific computing tools.
• Ability to independently investigate complex technical challenges and rapidly prototype solutions.
• Strong written and verbal communication skills.
• Experience with audio signal processing, acoustics, speech processing, or music information retrieval.
• Familiarity with MLOps practices, including experiment tracking, model versioning, CI/CD workflows, or scalable training infrastructure.
• Experience deploying machine learning models to embedded, edge, mobile, cloud, or realtime systems.
• Experience with full-stack software development and cloud technologies.
• Publications, open-source contributions, or demonstrated research achievements are a plus.
• Applicants for this position must be currently authorized to work in the United States on a full-time basis. Shure will not sponsor applicants for this position for work visas.

Pay

Each internship has an hourly rate which varies from $23-$43 per hour based on job function (Engineering, IT, Business, etc) and year completed in school (Junior, Masters 2nd year, PHD, etc).

Benefits

• Retirement savings plans
• Paid time off
• Employee discounts
• Professional development opportunities
• Work-life balance initiatives