Bose is looking for a Machine Learning/DSP Engineer Intern to help build their next generation of wearable and out-loud product experiences, enabling people to hear better, relish musical experiences, and achieve more.
Requirements
- Strong experience with programing in Python and MatLab.
- Strong experience with TensorFlow or PyTorch.
- Familiar Machine Learning, including deep learning neural networks, transfer learning, and training data development.
- Familiar with real time processing applications.
- Familiar with room acoustics physics and measurements
- Demonstrated Machine Learning Engineer experience via an internship, co-op, class, or personal project.
- Knowledge of embedded DSP.
Responsibilities
- Develop and evaluate DSP and Machine Learning algorithms with a focus on room acoustic applications.
- Research, implement and evaluate a variety of published approaches and algorithms for problems in DSP, Machine Learning, and audio signal processing.
- Collect and modify databases using physics-based analysis
- Develop machine learning models, training data, and evaluation infrastructure.
- Implement real time demo-able experience on prototyping platforms
Other
- Currently in the process of obtaining, a M.S., or PhD in Electrical Engineering, Acoustic Engineering, Computer Science, or related field.
- Experience with cross-group and cross-culture collaboration.
- High levels of creativity and quick problem-solving capabilities.
- Knowledge of C/C++, and bash scripting
- Music or Acoustic experience and interests
