Job description

At Bose Corporation, we believe sound is the most powerful force on earth — and for over 60 years, we have been a company built on innovation, excellence, and independence. Privately owned, fiercely customer-focused, and driven by our values, we continue to lead industries and transform lives through sound. Today, Bose Corporation is entering an exciting new era. Across multiple global Business Units and Global Functions, we are shaping the future of audio technology, automotive, luxury, and premium experiences. We invite you to join us in this transformation. Job Description Principal Audio DSP/ML Engineer - Audio Technology We are seeking a Principal Audio DSP / Machine Learning Applied Scientist to invent, develop, and productize advanced audio technologies. In this role, you will combine signal processing, machine learning, and systems engineering to deliver high-quality audio solutions for real-world consumer devices. You will work across the full pipeline—from algorithm research and deployment to optimized, real-time deployment on production hardware. 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: Design and develop audio signal processing and machine learning algorithms for speech and audio applications such as noise suppression, echo cancellation, beamforming, spatial audio, and audio enhancement Apply primarily modern ML/deep learning approaches augmented by classical DSP techniques to audio and time-series data. Investigate new modeling approaches and translate research ideas into practical, scalable solutions that will be experienced by millions of consumers. Qualifications: Bachelor’s degree in Electrical Engineering, Computer Engineering, Computer Science, Applied Mathematics , or related field. Hands-on experience with machine learning applied to audio or time-series data . Strong fundamentals in digital signal processing (sampling, filtering, FFTs, spectral analysis). Experience with Python and/or MATLAB for research and prototyping. Solid understanding of audio systems and acoustics . Strong communication skills. Preferred Qualifications: MS or PhD in a relevant technical field. Deep practical knowledge of: Applied ML frameworks such as PyTorch/ONNX and/or TensorFlow/TFLite . Audio DSP (sampling, filtering, FFTs, spectral analysis) using tools such as Python, Matlab and/or C/C . Experience with speech or audio ML tasks , such as: Audio source separation / speech enhancement Echo reduction Microphone array signal processing Strong software engineering practices (debugging, profiling, version control). Proficiency in C and/or C for performance-critical systems. Publications, patents, or demonstrated innovation in DSP or ML. What success looks like: You deliver robust, high-quality audio algorithms that work reliably in real-world conditions. You balance audio quality, ML performance, and system constraints effectively. You influence product direction through technical insight and data-driven decisions. Your work ships as both licensed audio technology at scale . At Bose, you're inspired to be and do your best and are rewarded for your unique talents! Our compensation is thoughtfully tailored to your skills, experience, education, and location, and goes beyond base salary. The hiring range for this position in the primary work location of Remote, California is: $216,000-$297,000.The hiring range for other Bose work locations may vary. In addition to competitive base pay we offer rewards including bonus programs, comprehensive health and welfare benefits, a 401(k) plan, plus exclusive perks designed to support your wellbeing, and a generous employee discount where you can immerse yourself in our products and experiences. We are a proudly independent company—driven by purpose, guided by our values, and united by a belief in the power of sound. As the world leader in audio experiences, we’re creating what’s next—pushing boundaries and delivering transformative sound experiences for people everywhere. Join us and make your next career move a mic-drop. Let’s Make Waves. ‎

Requirements

Must-haves

Principal Audio DSP/ML Engineer - Audio Technology
Design and develop audio signal processing and machine learning algorithms for speech and audio applications such as noise suppression, echo cancellation, beamforming, spatial audio, and audio enhancement
Apply primarily modern ML/deep learning approaches augmented by classical DSP techniques to audio and time-series data.
Investigate new modeling approaches and translate research ideas into practical, scalable solutions that will be experienced by millions of consumers.
Bachelor’s degree in Electrical Engineering, Computer Engineering, Computer Science, Applied Mathematics , or related field.
Hands-on experience with machine learning applied to audio or time-series data .
Strong fundamentals in digital signal processing (sampling, filtering, FFTs, spectral analysis).
Experience with Python and/or MATLAB for research and prototyping.
Solid understanding of audio systems and acoustics .
Strong communication skills.
You deliver robust, high-quality audio algorithms that work reliably in real-world conditions.
You balance audio quality, ML performance, and system constraints effectively.
You influence product direction through technical insight and data-driven decisions.
Your work ships as both licensed audio technology at scale .

Nice-to-haves

MS or PhD in a relevant technical field.
Deep practical knowledge of: Applied ML frameworks such as PyTorch/ONNX and/or TensorFlow/TFLite .
Audio DSP (sampling, filtering, FFTs, spectral analysis) using tools such as Python, Matlab and/or C/C .
Experience with speech or audio ML tasks , such as: Audio source separation / speech enhancement
Echo reduction
Microphone array signal processing
Strong software engineering practices (debugging, profiling, version control).
Proficiency in C and/or C for performance-critical systems.
Publications, patents, or demonstrated innovation in DSP or ML.

Application prep

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Keywords to mirror

mlmachine learningpython

Platform: workday
Effort: long

Benefits

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401(K)