Posted:
9/19/2024, 2:15:19 AM
Location(s):
Massachusetts, United States ⋅ Framingham, Massachusetts, United States
Experience Level(s):
Internship
Field(s):
AI & Machine Learning
You know the moment. It’s the first notes of that song you love, the intro to your favorite movie, or simply the sound of someone you love saying “hello.” It’s in these moments that sound matters most.
At Bose, we believe sound is the most powerful force on earth. We’ve dedicated ourselves to improving it for nearly 60 years. And we’re passionate down to our bones about making whatever you’re listening to a little more magical.
The engineering team at Bose is a thriving, passionate, deeply skilled team of professionals from a broad range of disciplines and experiences, who share a common goal—to create products that provide transformative sound experiences.
THE PROGRAM
We're looking for students to join our Internship Program who are obsessively curious about 'what's next'. You'll get hands on experience with our products and learn from the best of the best in the business. You will complete a specific project in 10-12 weeks with us, while integrating into your team. By the time you end your time with us, you will have been given the opportunity to truly make a real impact in the future of Bose and your career!
Opportunities don't stop at your day-to-day work. While you're getting a targeted look at your area of expertise, we'll expose you to other areas of the company. Our interns are given the opportunity to connect with senior leadership across the business to understand different perspectives at Bose. You'll network with other interns and colleagues to grow your network for the future!
Timeframe - June-August 2025
THE ROLE
We are looking for a audio machine learning research intern to join our research lab this summer! In this role you will help build our next generation of wearable and software products that are empowered by deep learning, enabling people to hear better, focus better and achieve more.
Responsibilities
Develop, train, and evaluate deep learning algorithms with a focus on audio problems such as acoustic scene classification and sound event detection.
Research, implement and evaluate a variety of published approaches and algorithms for problems in ML and audio signal processing.
Minimum Qualification
Recent graduate or currently is in the process of obtaining a M.S. or PhD in computer science, electrical engineering, machine learning, music technology, or related field.
Strong programming background with 2+ years of experience in Python.
Strong experience in implementing deep neural networks with Tensorflow, Keras, PyTorch, etc.
Familiar with latest research in deep learning for audio and ability to implement published algorithms
Experience with cross-group and cross-culture collaboration.
High levels of creativity and quick problem-solving capabilities
Preferred Qualification
Demonstrated software engineer experience via an internship, work experience, coding competitions.
Strong publication record demonstrating innovative research in venues such as DCASE, ISMIR, ICASSP, etc.
Strong knowledge and experience working with audio and digital signal processing
Our goal is to create an atmosphere where every candidate feels supported and empowered in the interviewing process. Diversity and inclusion are integral to our success, and we believe that providing reasonable accommodation is not only a legal obligation but also a fundamental aspect of our commitment to being an employer of choice. We recognize that individuals may have different needs and requirements based on their abilities, and we provide reasonable accommodations to ensure ideal conditions are met during the application process.
If you believe you need a reasonable accommodation, please send a note to [email protected]
Website: http://www.bose.com/
Headquarter Location: Framingham, Massachusetts, United States
Employee Count: 10001+
Year Founded: 1964
IPO Status: Private
Last Funding Type: Equity Crowdfunding
Industries: Audio ⋅ Consumer Electronics ⋅ Hardware ⋅ Manufacturing ⋅ Music