DSP/ML Research Engineer Co-op | Spring 2027
About the role
At Bose Corporation, we believe sound is the most powerful force on earth — and for over 60 years, we have been a company built on innovation, excellence, and independence. Privately owned, fiercely customer-focused, and driven by our values, we continue to lead industries and transform lives through sound.
Today, Bose Corporation is entering an exciting new era. Across multiple global Business Units and Global Functions, we are shaping the future of audio technology, automotive, luxury, and premium experiences. We invite you to join us in this transformation.
Job Description
DSP/ML Research Engineer Co-op | Spring 2027
We are looking for a Machine Learning/DSP Engineer Co-op to join our research lab this spring! In this role you will help build our next generation product experiences enabling people to hear better, relish musical experiences, and achieve more. The duration of this position is 6 months starting January 2027 (full-time 40 hours/week).
Responsibilities
- Research, implement and evaluate of multimodal fusion methods of sensors for environmental sensing.
- Develop and evaluate DSP and Machine Learning algorithms with a focus on room environmental sensing application.
- Collecting data using a variety of sensors such as microphones, IMUs, and light based systems.
- Develop machine learning models, training data, and evaluation infrastructure.
- Implement real time demo-able experience on prototyping platforms.
Minimum Qualification
- Currently in the process of obtaining a M.S., or PhD in Electrical Engineering, Acoustic Engineering, Computer Science, or related field.
- Strong experience with programing in Python and MatLab.
- Strong experience with TensorFlow or PyTorch.
- Experience with camera and IMU data collection and signal processing.
- Familiar with Machine Learning, including deep learning neural networks, memory constrained models, and training data development.
- Familiar with real time processing applications.
- Familiar with acoustic modeling.
- Experience with cross-group and cross-culture collaboration.
- High levels of creativity and quick problem-solving capabilities.
Preferred Qualification
- Demonstrated Machine Learning Engineer experience via an internship, co-op, class, or personal project.
- Knowledge of embedded DSP.
- Knowledge of C/C++, and bash scripting
- Music or Acoustic experience and interests
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