Principal Research Scientist (Hybrid - Shakopee, MN)

GN Group-posted 1 day ago
Full-time • Principal
Hybrid • Shakopee, MN
101-250 employees
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Principal Research Scientist Shakopee, MN – GN North American Headquarters (Hybrid) In the role of Principal Research Scientist on our GN research team, you will contribute to our purpose of Bringing People Closer. You will be one of the technical anchors for our signal processing roadmap – designing, implementing, and validating state‑of‑the-art audio and hearing‑aid algorithms that significantly improve speech intelligibility, listening comfort, robustness, and sound quality in challenging real-world environments. You will help set the technical direction for core hearing‑aid features and turn complex ideas into reliable solutions used daily by people with hearing loss worldwide. The team you will be part of: You will join a high‑impact research team within GN, working closely with signal processing, machine learning, acoustics, audiology, data science, and spatial sound in Shakopee and across our global organization. Our culture is ambitious, open, and customer‑obsessed. We: Use scientific rigor and data to challenge assumptions. Collaborate across disciplines to solve hard technical problems. Take pride in shipping robust, well‑engineered features – not just prototypes. Aspire to continuously raise the bar on our technology and ourselves, and we expect you to play an active role in shaping both. Your contribution is appreciated, and you will:

  • Own the design and optimization of advanced digital signal processing algorithms for hearing instruments, including (but not limited to) multi‑band amplification, adaptive feedback cancellation, single‑ and multi‑mic noise reduction, beamforming, and speech enhancement.
  • Lead the end‑to-end algorithm lifecycle: from concept and simulation in Matlab/Python, to fixed‑point implementation in C/C++/assembly on embedded hearing‑aid platforms to verification in lab and field.
  • Act as a key binding link between research, development, electro‑acoustic engineering, audiology, and product management, translating user and business needs into clear algorithm requirements and concrete technical designs.
  • Drive and support the development of machine‑learning‑based features for noise reduction and speech enhancement, including dataset strategy, feature design, evaluation metrics, and integration of models into embedded platforms.
  • Design and analyze perceptual listening tests to evaluate intelligibility, sound quality, and user preference in realistic acoustic environments, and use the results to iterate algorithm design.
  • Document architectures, design rationales, and test results with a level of clarity that enables reuse, maintenance, and regulatory documentation.
  • Act as a senior technical mentor – reviewing designs and code, sharing best practices in DSP, and helping grow the competence level of the broader engineering organization.
  • Have a PhD in Applied Physics, Electrical Engineering, Acoustics, Signal Processing, or a related field, with a strong focus on audio, speech, or hearing technologies.
  • Have deep, hands‑on expertise in digital signal processing for audio and speech, including core algorithms such as: Adaptive feedback/echo cancellation Multi‑band dynamic range compression Single‑ and multi‑channel noise reduction Beamforming and microphone array processing Speech enhancement in non‑stationary noise
  • Are very comfortable moving between theory and implementation: deriving, analyzing, and simulating algorithms – and then implementing, profiling, and debugging them on constrained embedded platforms.
  • Have strong programming skills in Matlab and C, and solid experience with at least one of C++, Python, R, or embedded assembly on DSP platforms.
  • Understand hearing‑aid‑relevant electro‑acoustics in practice and can design, execute, and interpret electro‑acoustic measurements, including test setups, calibration, and regression test design.
  • Bring experience with, or strong interest in, applying machine learning to audio and speech (e.g. DNN‑based noise reduction or speech enhancement) and can work effectively with development to make solutions deployable on low‑power devices.
  • Communicate clearly and concisely in spoken and written English and can adjust your message for different audiences – from deep‑dive technical discussions to clear explanations for non‑experts.
  • Are driven by solving real‑world problems for people with hearing loss and have a natural curiosity to learn, experiment, and continuously improve both your own skills and the solutions you work on.
  • Have solid understanding and hands‑on experience with modern software engineering frameworks and ways of working (e.g. version control, code review, CI/CD, testing practices, and agile methods), and know how to apply them in algorithm and embedded DSP development.
  • Commercial hearing aids or other regulated medical audio devices, including fitting software and electro‑acoustic verification frameworks.
  • Industry‑standard hearing‑aid platforms and toolchains from concept through to product launch.
  • Perceptual testing methodologies, user studies, or close collaboration with audiologists and hearing care professionals.
  • Patents, scientific publications, standards work (e.g. IEC), or representation in cross‑industry working groups.
  • annual bonuses
  • health insurance
  • a 401(k) plan
  • paid vacation and holidays
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