We are looking for a talented and driven individual to work on Audio signal processing and HW/SW technologies. The role focuses on evaluating, testing, and improving audio systems for various communication devices. The work involves firmware testing, acoustic tuning, audio evaluation, bug investigation, and contributing to the development of innovative products.
By joining us, you will have the opportunity to work on cutting-edge technologies in a collaborative and supportive team environment. We offer potential for growth and development, and the chance to contribute to a company that values diversity and innovation.
Responsibilities
- Conduct performance analysis and optimization of audio processing systems.
- Audio tuning of devices for real time communication optimization.
- Perform system acoustic evaluations and subjective analysis across various devices.
- Measure and analyze audio characteristics, performance and quality on different operating systems and devices.
- Develop and maintain evaluation pipelines and dashboards for audio testing.
- Document and communicate test results and debugging processes in reports.
- Provide technical support for audio systems using different lab set-ups and audio tools.
- Contribute to the development of innovative products.
Required Qualifications
- Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field.
- Background in audio signal processing.
- Proficiency in coding with C++ and/or Python.
- Familiar with audio systems and technologies.
- Knowledge of embedded systems and OS.
- Ability to set up and conduct lab experiments and evaluations.
- Strong technical skills and a willingness to learn new technologies.
- Excellent teamwork and communication abilities.
- Great problem-solving and analytical skills.
- Strong communication and collaboration skills.
Preferred Qualifications
- Experience with various audio devices used in communication systems.
- Experience with firmware testing and debugging processes.
- Experience with Artificial Intelligence (AI) and Machine Learning (ML) technologies.