Bose
Machine Learning & Digital Signal Processing Research Intern
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 more than 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 goalto create products that provide transformative sound experiences. Job Description
The Role We're looking for a Machine Learning (ML) & Digital Signal Processing (DSP) Research Intern to join the Advanced Systems Research group to work within the Automotive Active Sound Management space. In this role, the selected candidate will help us develop novel solutions for noise cancellation in cars by leveraging current advances at the intersection of ML and noise control. This person will design and validate new algorithms to improve noise cancellation performance, customization, scalability, and generalizability of deployed solutions. The primary working language will be Python and/or MATLAB with an ML backend of TensorFlow/Pytorch. They will be responsible for collaborating with others in the team and working at the interface of DSP and ML based algorithms. This person will need to be comfortable working with large amounts of data collected in the laboratory and in the field. Part of their work may involve working with hardware during model deployment. This work will have a direct impact across the automotive division as well as other divisions focused on noise cancellation using hybrid DSP-ML techniques. Additional responsibilities will include: Literature review of latest advancements in ML based algorithms for noise control applications Help modularize our current classical-DSP based solutions using machine learning Build on existing framework and deliver a deployable model on hardware Requirements To be successful in this role, you should be/have: Masters degree in Electrical Engineering, Computer Science, Acoustical Engineering, Mechanical Engineering, or a related field. Strong working knowledge of Machine Learning and Data Analysis supported by a background in Digital Signal Processing. Basic and advanced courses in ML and DSP. Strong communication skills with a proven track record of publishing research articles. Preferred Qualifications: Doctoral degree, 3rd year PhD and above Bose is an equal opportunity employer. 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.
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 more than 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 goalto create products that provide transformative sound experiences. Job Description
The Role We're looking for a Machine Learning (ML) & Digital Signal Processing (DSP) Research Intern to join the Advanced Systems Research group to work within the Automotive Active Sound Management space. In this role, the selected candidate will help us develop novel solutions for noise cancellation in cars by leveraging current advances at the intersection of ML and noise control. This person will design and validate new algorithms to improve noise cancellation performance, customization, scalability, and generalizability of deployed solutions. The primary working language will be Python and/or MATLAB with an ML backend of TensorFlow/Pytorch. They will be responsible for collaborating with others in the team and working at the interface of DSP and ML based algorithms. This person will need to be comfortable working with large amounts of data collected in the laboratory and in the field. Part of their work may involve working with hardware during model deployment. This work will have a direct impact across the automotive division as well as other divisions focused on noise cancellation using hybrid DSP-ML techniques. Additional responsibilities will include: Literature review of latest advancements in ML based algorithms for noise control applications Help modularize our current classical-DSP based solutions using machine learning Build on existing framework and deliver a deployable model on hardware Requirements To be successful in this role, you should be/have: Masters degree in Electrical Engineering, Computer Science, Acoustical Engineering, Mechanical Engineering, or a related field. Strong working knowledge of Machine Learning and Data Analysis supported by a background in Digital Signal Processing. Basic and advanced courses in ML and DSP. Strong communication skills with a proven track record of publishing research articles. Preferred Qualifications: Doctoral degree, 3rd year PhD and above Bose is an equal opportunity employer. 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.