Audio Machine Learning Research Engineer Intern

ABOUT BOSE

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 2024

THE ROLE

We are seeking a motivated Audio Machine Learning Research Engineer Intern to join our team and contribute to an exciting project focused on improving the performance of lightweight audio machine learning models utilizing model compression techniques such as knowledge distillation, model pruning, and quantization. As a part of our team, you will be immersed in cutting-edge research and development, working at the intersection of audio signal processing, machine learning, and the end-user experience. The duration of this position is 3 months, starting June 2024 (full-time 40 hours/week).

Responsibilities

• Implement and evaluate state-of-the-art model compression techniques to maximize the performance of lighter-weight audio understanding models to enable magical experiences on hardware.
• Research, implement and evaluate various published approaches and develop new approaches to optimize deep learning models for specific audio problems.­
• Work closely with the team to share progress, insights, and findings regularly through presentations and discussions.

Minimum Qualifications

• Recently graduated from, or is in the process of obtaining a M.S. or PhD in Computer Science, Electrical Engineering, Machine Learning, Music Technology, or a related field.
• Strong programming background with 2+ years of experience in Python and C/C++.
• Strong experience in implementing deep neural networks with PyTorch or Tensorflow.
• Experience with cross-group and cross-culture collaboration.
• High levels of creativity and quick problem-solving capabilities.

Preferred Qualification

• Proven software engineer experience via an internship, work experience, and coding competitions.
• Strong publication record in relevant venues (e.g., ICLR, ISMIR, ICASSP) demonstrating innovative research.
• Solid understanding and experience working with audio and digital signal processing.