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- Tasks: Prototype and implement AI-powered audio processing algorithms for real-time applications.
- Company: Join Bose Corporation, a leader in innovative audio technology.
- Benefits: Gain hands-on experience, network with professionals, and contribute to impactful projects.
- Why this job: Shape the future of audio technology while working with cutting-edge machine learning.
- Qualifications: Pursuing a graduate degree in ML, Computer Science, or related fields.
- Other info: Collaborative environment with opportunities to present at top-tier conferences.
Overview
Join to apply for the Audio Machine Learning Research Co-op role at Bose Corporation
We’re looking for students to join our Co-Op Program who believe that sound is power. Over the 6-month co-op, you will get the opportunity to apply the skills you learned in the classroom with hands-on work experience. Our Co-Ops will get to network across the business to understand different perspectives at Bose. You\’ll connect with other Co-Ops and colleagues to grow your network for the future!
Timeframe – Spring Co-op: Must be available January 12 – June 26, 2026
Role
The goal of our team is to develop novel AI-powered audio processing algorithms. The twist is that our algorithms must run in real-time, on physical devices, for applications such as voice pickup, hearing augmentation and ones we haven\’t even thought of yet. As part of the team, you will work with experts in machine learning (ML), digital signal processing (DSP), software engineering 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 are looking for candidates passionate about machine learning and audio to help us shape the next chapter in the future of Bose!
Responsibilities
- Most of your time will be devoted to prototyping, implementing and evaluating ML algorithms, curating and developing internal resources, and presenting your findings.
- You will integrate your novel solutions into existing systems and platforms to showcase new (proof of concept) solutions.
- You will be able to contribute to projects, which will be shipped to Bose customers, apply for patents, and/or submit papers to top-tier AI and signal processing conferences (e.g., NeurIPS, ICASSP, Inter Speech, etc.).
Requirements
- Education: Pursuing or recently finished a graduate-level degree in ML, Computer Science, Music Technology or a related field.
- Skills: Practical knowledge of:
- Applied audio ML (TensorFlow/PyTorch, TFLite/ONNX is a plus)
- Audio DSP (Python, Matlab and/or C/C++)
- Hands-on experience in at least one of the following research topics: Audio source separation, Speech enhancement, Microphone array signal processing, Tiny ML, Generative audio modelling
- Familiarity with methods for spatial sound synthesis and/or room acoustics simulation/analysis is a plus.
- Strong communication skills. You will be presenting your work to a large interdisciplinary community.
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. The EEOC’s “Know Your Rights: Workplace discrimination is illegal” Poster is available here: https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf. Bose is committed to providing reasonable accommodations to individuals with disabilities. If you require reasonable accommodation in completing this application, interviewing, completing any pre-employment testing, or otherwise participating in the employee selection process, please direct your inquiries to applicant_disability_accommodationrequest@bose.com. Please include \”Application Accommodation Request\” in the subject of the email.
Our goal is to create an atmosphere where every candidate feels supported and empowered in the interviewing process. Diversity and inclusion are integral to our success, and we believe that providing reasonable accommodation is not only a legal obligation but also a fundamental aspect of our commitment to being an employer of choice. We recognize that individuals may have different needs and requirements based on their abilities, and we provide reasonable accommodations to ensure ideal conditions are met during the application process.
Seniority level
- Internship
Employment type
- Full-time
Job function
- Other
Industries
- Computers and Electronics Manufacturing
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Audio Machine Learning Research Co-op employer: Bose Corporation
Contact Detail:
Bose Corporation Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Audio Machine Learning Research Co-op
✨Tip Number 1
Network like a pro! Reach out to current or past Co-Ops at Bose on LinkedIn. Ask them about their experiences and any tips they might have for you. This can give you insider knowledge and help you stand out.
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your projects related to audio ML or DSP. When you get the chance to chat with interviewers, share your work and how it relates to what Bose is doing. It’s all about making that connection!
✨Tip Number 3
Practice makes perfect! Get comfortable discussing your technical skills and projects. Mock interviews with friends or mentors can help you articulate your thoughts clearly and confidently when it’s your turn to shine.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re serious about joining the Bose team. Let’s make it happen!
We think you need these skills to ace Audio Machine Learning Research Co-op
Some tips for your application 🫡
Show Your Passion for Audio and ML: When you're writing your application, let your enthusiasm for audio and machine learning shine through! Share any relevant projects or experiences that highlight your skills and passion for the field. We want to see how you connect with our mission at Bose.
Tailor Your CV and Cover Letter: Make sure to customise your CV and cover letter for this specific role. Highlight your experience with audio processing, machine learning, and any relevant programming languages. We love seeing candidates who take the time to align their skills with what we’re looking for!
Be Clear and Concise: Keep your application clear and to the point. Use straightforward language and avoid jargon unless it’s necessary. We appreciate candidates who can communicate complex ideas simply, especially since you'll be presenting your work to a diverse audience.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way to ensure your application gets into the right hands. Plus, it shows us that you’re serious about joining our team at Bose.
How to prepare for a job interview at Bose Corporation
✨Know Your Stuff
Make sure you brush up on your knowledge of audio machine learning and digital signal processing. Familiarise yourself with the latest algorithms and tools like TensorFlow or PyTorch. Being able to discuss your projects and how they relate to Bose's goals will show your passion and expertise.
✨Showcase Your Projects
Prepare to talk about any relevant projects you've worked on, especially those involving audio ML or DSP. Bring examples that demonstrate your hands-on experience and problem-solving skills. If you can, share insights on how your work could apply to real-time audio processing at Bose.
✨Practice Your Presentation Skills
Since strong communication is key for this role, practice explaining complex concepts in simple terms. You might be asked to present your findings, so being clear and engaging will help you stand out. Consider doing mock presentations with friends or mentors to get comfortable.
✨Ask Thoughtful Questions
Prepare some insightful questions about Bose's projects and future directions in audio technology. This shows your genuine interest in the company and the role. It’s also a great way to demonstrate your critical thinking and enthusiasm for contributing to their innovative team.