Deep Learning Engineer

Join our AI/ML team in Staefa, Switzerland, as a Deep Learning Engineer. Help create innovative hearing solutions for millions worldwide!, We want to grow our AI/ML team to deliver empowering hearing solutions to millions of people worldwide. In our international team we develop deep learning solutions for the next generation of hearing aids.

Are you an enthusiastic engineer with fresh ideas, ready to take on new challenges to push the current technology forward?

Do you want to be part of a team that will revolutionize the hearing experience for millions of people with hearing disabilities?

Are you a researcher who wants to go all the way from the initial idea to a real-life embedded device?

More about the role *

Design, implement, evaluate, test and deploy DNN models and software prototypes *

Develop code in a collaborative environment supporting CI/CD workflows *

Support the development of embedded solutions, working at the interface between machine learning tools and embedded systems. *

Engage in team collaboration to meet joint goals like product integration, collaborate across different R&D sites, As one of the world's leading hearing care providers headquartered in Switzerland, we're committed to building an inclusive culture.

We can offer you a new challenge, with interesting tasks and much more - including an open corporate culture, flat hierarchies, support for further training and development, opportunities to take on responsibility, an excellent range of foods, sports and cultural facilities, attractive employment conditions, and flexible working time models in various roles.

• Master's or PhD in a relevant field with 2+ years of deep learning experience.
• Fluent in advanced TensorFlow/Keras or PyTorch concepts.
• Communication skills in English with team collaboration experience., Master's or PhD degree in computer science, electrical engineering, or related technical discipline

2+ years of experience in deep learning and fluent in advanced TensorFlow/Keras or PyTorch concepts *

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 *

Experience with Unix automation tools, DevOps/MLOps is a plus