DSP/ML Research Engineer Co-op
About The Position
ABOUT THE CO-OP PROGRAM Bose Corporation is seeking students to participate in our Co-op Program who share our belief that sound is power. During the six-month co-op, students will have the chance to apply classroom learning in a hands-on work environment. Co-op participants will network across the business to gain diverse perspectives within Bose Corporation. Additionally, co-ops will connect with other students and colleagues, building valuable professional relationships for the future. Fall Co-op: Candidates must be available to work full-time (40 hours per week) in a hybrid, in-office format from July 13 through December 18, 2026. No relocation assistance is available. THE ROLE 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 of wearable and out-loud product experiences enabling people to hear better, relish musical experiences, and achieve more. The duration of this position is 6 months starting July 2026 (full-time 40 hours/week).
Requirements
- 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 Pyroomacoustics, COMSOL or similar acoustic modeling packages
- Familiar Machine Learning, including deep learning neural networks, transfer learning, and training data development.
- Familiar with real time processing applications.
- Familiar with room acoustics, geometric, and wave based acoustic modeling.
- Experience with cross-group and cross-culture collaboration.
- High levels of creativity and quick problem-solving capabilities.
Nice To Haves
- 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
Responsibilities
- Develop and evaluate DSP and Machine Learning algorithms with a focus on room acoustic applications.
- Develop acoustic simulations experiments using common simulation packages.
- Research, implement and evaluate a variety of published approaches and algorithms for problems in DSP, Machine Learning, and audio signal processing.
- Develop machine learning models, training data, and evaluation infrastructure.
Benefits
- comprehensive health and welfare benefits
- a 401(k) plan
- exclusive perks designed to support your wellbeing
- a generous employee discount where you can immerse yourself in our products and experiences
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What This Job Offers
Job Type
Full-time
Career Level
Intern
