Data Engineering Intern

Shure•Niles, IL

4d•$23 - $43•Hybrid

About The Position

The research science team seeks a motivated engineer to create, augment, and simulate audio data. In your role as Data Engineer Intern, you will closely collaborate with research scientists who conduct audio machine learning experiments, and you will also participate in the creation and maintenance of scalable data infrastructure. This position offers an excellent opportunity for you to gain hands-on experience working with research scientists in data engineering while working in a collaborative environment on innovative technologies supporting data science. This Internship is Hybrid in Niles, IL.

Requirements

In progress of completing a Bachelor's or master's degree in computer science, mathematics, digital signal processing, or related field with coursework or experience in data engineering.
Experience with programming languages such as Python.
Understanding of relational databases and/or experience with database architectures like PostgreSQL or Snowflake.
Applicable academic or professional experience in audio-related disciplines such as room acoustics, audio signal processing, microphone and mic array characteristics, psychoacoustics, or music production.
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.

Nice To Haves

Some experience and understanding of cloud-based services like AWS and related tools is a plus.
Experience with simulating and testing audio systems with mathematical modelling languages such as Python or MATLAB is a plus.
Creativity and curiosity for future technologies while having a strong core of fundamentals.

Responsibilities

The intern will engineer software modules that provide data mechanisms to support research and prototyping of forward-leaning use cases in audio machine learning algorithms.
Working closely with our data science and software engineering team to help generate new footing for data platforms and pipelines within our current architecture.