Machine Learning / AI Engineer

Bose Corporation, U.S.A•Us, MA

2d•Remote

About The Position

At Bose Corporation, the Machine Learning / AI Engineer helps develop intelligent capabilities for next-generation audio experiences. The role focuses on designing, training, testing, and optimizing machine learning models that work efficiently on devices with limited memory and computing power, combining Efficient AI and Edge ML. The engineer collaborates with teams across machine learning, software, embedded systems, and hardware, contributing ideas and learning how models move from experimentation toward deployment.

Requirements

A bachelor’s or advanced degree in Computer Science, Electrical Engineering, Machine Learning, or a related technical field.
At least 3 years of relevant machine learning or AI experience, which may include applicable research or substantial project work.
A solid foundation in machine learning and deep learning, with hands-on experience building and evaluating models.
Proficiency in Python and experience with a framework such as PyTorch or TensorFlow.
Experience training, evaluating, and debugging models.
An analytical approach to problem-solving, willingness to ask questions, and enthusiasm for working with others.

Nice To Haves

Experience with quantization, pruning, or model compression.
Experience with Edge ML, embedded AI, or deploying models on devices with limited computing resources.
Experience with C/C++ or deployment tools such as ONNX or TensorFlow Lite.
Experience with audio ML, speech processing, acoustic sensing, or related applications.
Familiarity with emerging AI technologies and AI-assisted engineering tools.

Responsibilities

Develop, train, and evaluate machine learning models for consumer audio applications.
Improve model accuracy while reducing latency, memory use, and computational demands.
Partner with software, embedded, and hardware engineers to help bring AI capabilities onto devices.
Analyze results, debug issues, and use testing to guide further experiments.
Explore emerging machine learning techniques, share findings, and contribute ideas to the team.