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Part-Time Student Worker in Audio Engineering with a Focus on Machine Learn at Elevear GmbH

Aachen, North Rhine-Westphalia, Germany -

Full Time

Start Date

Immediate

Expiry Date

04 Jan, 26

Salary

0.0

Posted On

06 Oct, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Audio Processing, Embedded Systems, Machine Learning, C/C++, Python, MATLAB, Code Optimization, Unit Testing, Debugging, Version Control, Acoustics, Audio Technology

Industry

Computers and Electronics Manufacturing

Description

We are seeking a motivated part-time student worker to support our technology development team in the field of audio engineering, with a focus on machine learning. This position offers the opportunity to gain practical experience in audio processing, embedded systems, and machine learning techniques. Ideal for students in Electrical Engineering, Computer Science, or related fields, this role allows you to balance academic commitments with hands-on industry experience. Tasks Assist in the implementation and testing of machine learning algorithms for adaptive Active Noise Cancellation, adaptive Transparency, Occlusion Cancellation, speech enhancement, noise reduction, and Spatial Audio. Contribute to code development and documentation in C/C++, Python, and MATLAB. Participate in code optimization tasks to improve efficiency and memory utilization. Support unit testing and debugging processes. Engage in learning opportunities in audio processing, embedded systems, and machine learning. Requirements Currently enrolled in a Bachelor’s or Master’s program in Electrical Engineering, Computer Science, or a related field. Basic knowledge of embedded systems programming, audio processing, and machine learning. Familiarity with programming languages such as C/C++, Python, and MATLAB. Willingness to learn and apply software development concepts, including version control systems like GIT. Strong interest in acoustics, audio technology, and machine learning. Benefits Gain practical experience in a dynamic and innovative startup environment. Flexible work hours to accommodate your academic schedule. Opportunity to work with leading companies in the hearables industry. Mentorship and guidance from experienced engineers.

Responsibilities

Assist in the implementation and testing of machine learning algorithms for various audio applications. Contribute to code development and documentation while engaging in learning opportunities in audio processing and machine learning.