Bose Corporation | Machine Learning Engineer Intern | Framingham, MA | United States | BigDataKB.com | 2023-02-01

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Job Location: Framingham, MA

Job Detail:

Job Description

ABOUT BOSE

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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. And we’ve dedicated ourselves to improving it for nearly 60 years. Ever since our founder, Dr. Amar Bose, bought a stereo system and thought, “I can make this better,” we’ve been relentlessly pushing forward to the next best thing.

Innovation is more than what we do. It’s who we are — constantly learning and constantly curious. We never stop imagining what better sound sounds like. We’re music fanatics and audio engineers. We’re explorers and inventors and dreamers. And we’re passionate down to our bones about making whatever you’re listening to a little more magical.

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 2023

THE ROLE

We are looking for an ML Research Engineer intern to join our research lab this summer! In this role you will help build our next generation of Bose 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.
  • Research, implement and evaluate a variety of published approaches and algorithms for problems in ML and audio signal processing.
  • Suggest, collect, and synthesize requirements to inform machine learning product roadmaps.

Minimum Qualification

  • Currently has, or is in the process of obtaining, a M.S. or PhD in Computer Science, Electrical Engineering, Machine Learning, or related field.
  • Strong programming background with 2+ years of experience in Python and C/C++.
  • 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

Preferred Qualification

  • Strong publication record in audio ML such as ISMIR, ICASSP, and DCASE
  • Strong knowledge and experience working with audio and digital signal processing

Bose is an equal opportunity employer that is committed to inclusion and diversity. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, genetic information, national origin, age, disability, veteran status, or any other legally protected characteristics. For additional information, please review: (1) the EEO is the Law Poster (http://www.dol.gov/ofccp/regs/compliance/posters/pdf/OFCCP_EEO_Supplement_Final_JRF_QA_508c.pdf); and (2) its Supplements (http://www.dol.gov/ofccp/regs/compliance/posters/ofccpost.htm). Please note, the company’s pay transparency is available at http://www.dol.gov/ofccp/pdf/EO13665_PrescribedNondiscriminationPostingLanguage_JRFQA508c.pdf. Bose is committed to working with and providing reasonable accommodations to individuals with disabilities. If you need a reasonable accommodation because of a disability for any part of the application or employment process, please send an e-mail to [email protected] and let us know the nature of your request and your contact information.

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