Audio Machine Learning Intern/Co-op

Bose Corporation; Atlanta (GA); Sur place; USD 55 000 - 70 000; Plein temps

Avantages offerts par ce poste

Employee discount

Health benefits

401(k) plan

Résumé du poste

Bose Corporation is seeking an Audio Machine Learning Intern to help develop the next generation of AI‑powered audio technologies. You will work with ML, DSP, software engineering, and psychoacoustics experts to research, prototype, and evaluate novel audio algorithms.

Your work may span areas such as speech enhancement, voice pickup, hearing augmentation, spatial audio, and real‑time machine learning. There is potential to contribute to future Bose products and publications.

Qualifications

• Currently pursuing or recently completed MS/PhD in a related field.
• Experience building ML models with PyTorch, TensorFlow or Keras.
• Proficient in Python; familiarity with C/C++/MATLAB.
• Understanding of audio signal processing fundamentals.
• Experience in audio ML areas such as speech enhancement or spatial audio.
• Strong problem solving, collaboration and communication skills.

Responsabilités

• Develop, train, and evaluate ML and DL algorithms for audio apps.
• Research and implement state‑of‑the‑art audio ML and DSP approaches.
• Prototype and integrate ML algorithms into software/hardware platforms.
• Develop and curate datasets, tools, and resources for ML research.
• Collaborate with researchers across disciplines to solve audio problems.
• Present findings and recommendations to Bose's interdisciplinary community.

Connaissances

Machine Learning

Python

PyTorch

DSP

C/C++

Team collaboration

Formation

MS/PhD in CS/EE/ML/Music Tech

Outils

PyTorch

TensorFlow

Keras

Description du poste

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

The Role

At Bose, we have a passion for creating extraordinary audio experiences by combining innovative research with cutting‑edge technology. We’re looking for an Audio Machine Learning Intern to help develop the next generation of AI‑powered audio technologies.

In this role you’ll work alongside experts in machine learning, digital signal processing, software engineering, and psychoacoustics to research, prototype, and evaluate novel audio algorithms. Your work may span areas such as speech enhancement, voice pickup, hearing augmentation, spatial audio, and new applications enabled by real‑time machine learning.

You’ll have the opportunity to take ideas from research through proof of concept, with the potential to contribute to future Bose products, patents, and research publications.

Responsibilities

• Develop, train, and evaluate machine learning and deep learning algorithms for audio applications.
• Research and implement state‑of‑the‑art approaches in audio ML and digital signal processing.
• Prototype and integrate ML algorithms into software or hardware platforms to demonstrate new audio experiences.
• Develop and curate datasets, tools, and resources to support ML research and evaluation.
• Collaborate with researchers and engineers across disciplines to solve challenging audio problems.
• Present research findings and technical recommendations to Bose's interdisciplinary community.

Minimum Qualifications

• Currently pursuing or recently completed an M.S. or Ph.D. in Computer Science, Electrical Engineering, Machine Learning, Music Technology, or a related field.
• Experience developing machine learning or deep learning models using PyTorch, TensorFlow, Keras, or similar frameworks.
• Programming experience with Python and familiarity with C/C++, MATLAB, or similar languages.
• Understanding of audio signal processing and/or digital signal processing fundamentals.
• Experience with at least one audio ML area, such as speech enhancement, source separation, microphone array processing, TinyML, generative audio, spatial audio, or audio perception.
• Strong problem‑solving, collaboration, and communication skills.

Preferred Qualifications

• Experience deploying ML models for real‑time or resource‑constrained applications, including TFLite, ONNX, or similar technologies.
• Experience with spatial audio, room acoustics, or acoustic simulation and analysis.
• Software engineering experience demonstrated through internships, research, coursework, or personal projects.
• Research publications or demonstrated research experience in machine learning, audio, or signal processing.
• Passion for audio, music, machine learning, and creating exceptional sound experiences.

TIMEFRAME

• January 11-June 25, 2027
• June 7- August 20, 2027
• July 12- December 17, 2027

At Bose, you're inspired to be and do your best and are rewarded for your unique talents! Our compensation is thoughtfully tailored to your skills, experience, education, and location, and goes beyond base salary. The hiring range for this position in the primary work location of Framingham, Massachusetts is: $40.00-$51.25 per hour.The hiring range for other Bose work locations may vary. In addition to competitive base pay we offer rewards including bonus programs, comprehensive health and welfare benefits, a 401(k) plan, plus exclusive perks designed to support your wellbeing, and a generous employee discount where you can immerse yourself in our products and experiences. We are a proudly independent company—driven by purpose, guided by our values, and united by a belief in the power of sound. As the world leader in audio experiences, we’re creating what’s next—pushing boundaries and delivering transformative sound experiences for people everywhere. Join us and make your next career move a mic‑drop. Let’s Make Waves.