Deep Learning Engineer

Training state-of-the-art deep learning models for hearing applications that provide optimal quality and efficiency on our embedded device platforms. Collaborate closely with adjacent teams to integrate deep learning models into the signal processing chain effectively while understanding their impact on overall hearing device performance. Develop code in a collaborative environment supporting CI/CD workflows. Contribute building our DNN training and development software toolchain. Evaluate model behavior on-device taking into account all relevant boundary conditions and system implications. Taking end-to-end ownership of deep learning projects from idea to product deliverable and provide guidance in technical discussions and code reviews.

At Sonova, we envision a world where everyone can enjoy the delight of hearing. This vision inspires us and fuels our commitment to developing innovative solutions that improve hearing health and human connection - from personal audio devices and wireless communication systems to hearing aids and cochlear implants. We're dedicated to providing outstanding customer experiences through our global audiological care services, ensuring that everyone has the opportunity to engage fully with the world around them. Guided by a culture of continuous improvement that fosters resilience and self-motivation, our team is united by a shared commitment to excellence and a deep sense of pride in our work, each of us playing a vital role in creating meaningful change. Here you’ll find a diverse range of opportunities that span both consumer and medical solutions and the freedom to shape your career while making an impact on the lives of others. Join us in our mission to create a more connected world, where every voice is heard and every story matters.

• Master’s or PhD degree in computer science, electrical engineering, or related technical discipline

• 2+ years of experience in deep learning

• Strong proficiency in Python and fluent in advanced TensorFlow/Keras or PyTorch concepts

• Hands-on experience at the boundary between deep learning and embedded systems

• Communication skills with full professional proficiency in English

• Education in audio or speech processing, and understanding of edge computing/low-power computation and embedded systems is a plus