Bose audio ML summer internship
zan...@gmail.com
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Bose - ML Engineer Intern | Summer 2022
Bose's mission is to empower people to focus more, feel more and achieve more by innovating the most magical audio technologies –– technologies that elegantly blend cutting-edge research in acoustics, digital signal processing, machine learning, software, and hardware.
Through our ecosystem of earbuds, headphones, and speakers in-the-home, on-the-go, and in-the-car, we are creating the most immersive audio technology to let people enjoy sound in a depth and quality they have never experienced before. By crafting more adaptive and personalized algorithms, we continue to uplift noise cancellation, creating a clean & noise-free canvas for artists to deliver astonishing sound with the fullest range and the finest texture. Through our innovation in self-fitting hear aids, we are bringing superpower to people, allowing people to focus on sound they care about while blocking out undesired noises. Our global research teams are constantly iterating, solving problems, and innovating to make these technologies better. Together, we can help empower people to focus more, feel more, and to achieve their fullest potential.
We are looking for an ambitious ML engineer to join Bose Research this summer! At Bose, we use machine learning across a diverse set of problems ranging from speech enhancement (e.g., Bose PinPoint) to audio perception. As a ML Engineer intern at Bose, you will help build our next generation of wearable and speaker products that are empowered by deep learning. The duration of this position is 12 weeks starting June 2022 (full-time 40 hours/week).
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.
Prune and compress deep learning models for deployment on edge devices.
Suggest, collect, and synthesize requirements to inform machine learning product roadmap.
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 the latest research in deep learning for audio and ability to implement published algorithms
Experience with cross-group and cross-culture teamwork.
High levels of creativity and quick problem-solving capabilities
Preferred Qualification
Proven software engineer experience via an internship, work experience, coding competitions.
Strong publication record demonstrating innovative research
Solid understanding and experience working with audio and digital signal processing