The ML team at Bose CE Applied Research is looking for a co-op to work on machine learning and deep learning for audio understanding as well as MIR for six months starting July 2021.
The applicant must be eligible to work in the US as an intern/co-op.
Contact: Please send your resume to Shuo Zhang (firstname.lastname@example.org).
Machine Learning Co-op Spring 2021
At Bose, we’ve spent more than 50 years finding new ways to bring pioneering audio products to millions of people in their homes, cars, planes, and just about anywhere else people enjoy their music. To succeed for the next 50 years, we must continue to drive innovation that delivers on our human-centered brand promise to help people be more, feel more, and do more.
The Machine Learning team in CED Applied Research at Bose is looking for a passionate Machine Learning Co-op to work at the intersection of Artificial Intelligence and User Experience. The duration of this position is 6 months starting July 2021 (full-time 40 hours/week).
What you can expect:
- Work as part of a passionate and collaborative team of ML, iOS, embedded, DSP, and cloud engineers
- Your vision will influence the direction of future Bose Consumer Electronics products
- Gain hands-on experience in applied machine learning and deep learning for audio, DSP, software engineering, model deployment, etc.
What you’ll do:
- Work on a focused six-month ML research project in audio signal processing with a mentor
- Work on a variety of audio understanding problems with machine learning and deep learning
- Prune and compress deep learning models for deployment on edge devices or embedded targets
- Research, implement, and evaluate a variety of published approaches and algorithms for problems in ML and audio signal processing
What we’re looking for:
- Strong programming background with 2+ years of experience in Python and/or Java
- Strong knowledge and experience working with audio and DSP preferred
- Undergraduate or graduate computer science, electrical engineering or related major with experience building ML systems for audio signal processing and/or music information retrieval applications
- Familiar with latest research in deep learning for audio and able to implement algorithms from research papers
- Strong experience in implementing deep neural networks with Tensorflow, Keras, PyTorch, etc.
- (Desired) Experience and interest in deploying models to edge devices
- (Desired) Experience and interest in working on audio perception problems such as speech enhancement, voice pick-up, SED/SELD, MIR, etc.
- (Desired) Publications in communities such as ISMIR, DCASE, ICASSP, etc.
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.