DSP & ML Research Intern — Multimodal Sensing

Bose Corporation, U.S.A; Framingham (MA); On-site; USD 55,000 - 71,000; Full time

Job summary

Bose Corporation in Framingham, MA is seeking a DSP/ML Research Engineer Intern for Summer 2027. The role involves researching, implementing, and evaluating multimodal fusion methods and developing DSP and ML algorithms for room environmental sensing, with data collection from microphones, IMUs, and light-based sensors.

You'll work in a collaborative research environment, applying Python, MATLAB, TensorFlow or PyTorch, and real-time processing techniques to build next-generation audio

Qualifications

• Pursuing an MS or PhD in EE, Acoustic Eng, CS, or related field.
• Strong Python and MATLAB programming experience.
• Experience with TensorFlow or PyTorch.
• Experience with camera/IMU data collection and signal processing.
• Familiar with ML, including deep learning neural networks, memory-constrained training.
• 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.

Responsibilities

• Research, implement and evaluate multimodal fusion methods of sensors for environmental sensing.
• Develop and evaluate DSP and Machine Learning algorithms with a focus on room environmental sensing.
• Data collection using microphones, IMUs, and light-based sensors.
• Develop machine learning models, training data, and evaluation infrastructure.

Skills

Python

Matlab

TensorFlow

PyTorch

Real-time processing

Acoustic modeling

Cross-group collaboration

Creativity

Education

MS/PhD in Electrical Engineering / Acoustic Engineering / CS

Tools

C/C++

bash scripting

Embedded DSP

Job description

Bose Corporation in Framingham, MA is seeking a DSP/ML Research Engineer Intern for Summer 2027. The role involves researching, implementing, and evaluating multimodal fusion methods and developing DSP and ML algorithms for room environmental sensing, with data collection from microphones, IMUs, and light-based sensors.

You'll work in a collaborative research environment, applying Python, MATLAB, TensorFlow or PyTorch, and real-time processing techniques to build next-generation audio