Machine Learning / Neural Audio Synthesis Internship 1147 views

Description

The goal of our team at Bose Hear is to explore new ways to allow individuals with hearing loss enhance their conversations and ultimately hear better in noisy environments. Our work centers on implementing and testing cutting edge deep learning algorithms for tasks such as source separation and speech enhancement. As part of the team you will be working with experts in machine learning, deep learning, digital signal processing and psychoacoustics to prototype and implement new algorithms.

Bose has a strong history of combining creative thinking with cutting edge technology in the audio domain. We’re looking for candidates passionate about ML and audio to help shape Bose’s next chapter!

Responsibilities

• As an intern on our team, a large chunk of your time will likely be devoted to prototyping and implementing ML and software based solutions and experiences. You will investigate novel algorithms, analyze and evaluate them against big data sets, help curate and develop large internal audio datasets, and present your results.
• In addition, you will integrate solutions into new and existing systems and platforms to show new proof of concepts.
• A big part of your job may also include researching and implementing model compression techniques to deploy algorithms on hardware and edge platforms.

Education

• Pursuing or just finished a degree in ML, Computer Science or a related field. Graduate level candidates preferred, but the position is really open to any student or recent grad with the right interest and skillset.
• Candidate should be familiar with material covered in introductory courses on linear algebra, statistics, digital signal processing and data structures.

Skills

• Able to develop in Python, Tensorflow and/or C/C++ (just R or Matlab won’t cut it)
• Strong understanding of Machine Learning and DSP concepts
• Familiar with standard development practices (version control, testing, micro-services)
• Strong communication skills and comfortable with presenting analyses to a wider group (you will have the opportunity to present your work on a regular basis).
• Familiarity with the some of the following technologies is also preferred: TensorFlow, Keras, AWS, Scikit-Learn, PyTorch, Git, Flask, Jupyter Notebooks, etc.
• Extra points for familiarity with the latest advances in neural audio synthesis, source separation, model compression.
• Interest/experience with implementing machine learning algorithms on hardware or edge devices a BIG plus.

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 Wellbeing@bose.com and let us know the nature of your request and your contact information.