Data Science (Audio) Intern

Key Skills

Algorithms, Deep Learning, Design of Experiment, Effective communication skills, Machine learning techniques, matplotlib, NumPy, Python Programming, PyTorch, Signal processing, spaCy, TensorFlow

Job Description

Shure offers a challenging, fun and rewarding summer internship program. The twelve-week program is offered to undergraduate students that have completed at least 2 years of college, as well as 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 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 Shure Strategic Technology Team is looking for a Data Science (Audio) Intern to help research, develop, and demonstrate novel product features and use cases enabled by machine learning and artificial intelligence. You will contribute to the data science group with AI-assisted enhancements to our applications in audio or joint audio/video, such as source separation, de-reverberation, blind room characterization, and more. The project may target devices such as conference call systems, work-from-home systems, headphones, microphones, and more.

We are a diverse group of engineers, scientists, designers, and people with other backgrounds who invent and prototype useful, playful, and beautiful things. Our vision is to make life easier, more connected, more entertaining, more personal, and more productive. This is your opportunity to join our talented professionals as an intern to work on cutting-edge technologies and cool projects.

This Internship can be Onsite or Hybrid.

Responsibilities

• Work collaboratively with data scientists and engineers to identify use cases of value that leverage machine learning and artificial intelligence.
• Research, build, train, and quantitatively/qualitatively assess deep learning models. 
• Identify and capture datasets from different sources for model development, which may include discovering, recording, simulating, cleaning, and pre-processing the data.
• Provide demonstrations of the concept, design, and results to peers and stakeholders.
• Document all design, experiments, and results.

Qualifications

• Completion of at least two years of coursework in Electrical or Computer Engineering, Computer Science, Mathematics, or related field with an emphasis in Data Science or Machine Learning preferred.
• An interest in audio is required, experience with audio of any kind preferred.
• Experience with Python’s scientific libraries (numpy, scipy, matplotlib, etc.)
• Experience with training and verifying machine learning and deep learning models in frameworks such as TensorFlow or PyTorch.
• Good verbal and written communication skills.