Audio Applied Research Science Intern

Shure • Niles, IL

73d • $21 - $40

About The Position

Shure offers a challenging, fun and rewarding summer internship program. The twelve-week program is offered to undergraduate and graduate students. We offer internships with a variety of work arrangements from onsite interns to fully remote in US. Each intern will receive a competitive salary. Additionally, Interns who are asked to relocate to Illinois for onsite internships will receive a housing stipend to cover living expenses. Applications will be collected, reviewed, and selected candidates will be contacted in late fall/early winter. The Signal Processing and Applied Research Science team seeks a skilled Audio Applied Research Science Intern to help build next-generation product features enabled by machine learning and artificial intelligence. This Internship can be Remote, Onsite, or Hybrid, based out of our Niles, IL headquarters.

Requirements

• In-process of a PhD or advanced Masters in electrical engineering, computer science, mathematics, statistics, physics, data science, machine learning or a related field.
• Deep experience in application of machine learning to audio, video, and/or other digital signal processing.
• Demonstrated experience with leading machine learning tools and libraries.
• A self-starter capable of digging deeply into ideas and concepts and generating rapid prototypes.
• Experience or understanding of common ML-Ops patterns is a plus.
• Experience with full stack development is a plus.
• Must be currently authorized to work in the United States on a full-time basis.

Responsibilities

• Work as part of a cross-functional team of data scientists and engineers to create, design & implement cutting-edge audio features and products.
• Solve problems through research, collection/creation of data, and through architecture, training, and evaluation of deep neural network models targeting audio functionality.
• Adapt models for implementation in a range of platform environments.
• Adopt mature machine learning software engineering practices.
• Record findings, results and notes in collaborative documentation tools.

Benefits

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

What This Job Offers

• Career Level: Intern
• Education Level: Ph.D. or professional degree
• Number of Employees: 1,001-5,000 employees