Deep Learning Engineer
Indexed description
Are you curious to explore these uncharted territories?
Are you an engineer who enjoys adapting and optimizing models to meet latency, memory, and power constraints?
Do you want to contribute to technology where every improvement has a direct impact on how people hear and interact with their environment?
If that speaks to you, we are looking for you, as our new colleague and deep learning engineer.
More About The Role
- 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
- 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
Sonova is an equal opportunity employer.
We team up. We grow talent. We collaborate with people of diverse backgrounds to win with the best team in the market place. We guarantee every person equal treatment in regard to employment and opportunity for employment, regardless of a candidate’s ethnic or national origin, religion, sexual orientation or marital status, gender, genetic identity, age, disability or any other legally protected status.
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