Sonova GruppeDeep Learning Engineers form the core of our team at Audatic. If you are excited to develop novel deep learning algorithms for audio processing, we have a fantastic job opportunity for you
Training state-of-the-art deep learning models that provide optimal quality and efficiency on our embedded device platforms.
Experimenting with novel approaches such as new types of neural network architectures, loss functions, datasets, and evaluation metrics.
Staying up to date with the latest innovations in deep learning research
Developing and conducting automated hyper-parameter optimizations on our dedicated GPU cluster and custom deep learning software stack.
Contributing to learning efforts in the team like our regular journal club, brainstorming sessions, and co-learning through online courses.
A bachelor's or master's degree in a technical field
At least 2 years of relevant experience
Strong proficiency in Python with a demonstrated ability to write robust, clean and maintainable code
Dependable communication skills with full professional proficiency in English
Experience with digital signal processing or audio processing is a plus
More About What We Offer
At Audatic, you'll be part of a diverse, international, and passionate team that values collaboration and innovation. We provide an environment that allows you to balance professional growth with personal well-being.
30 days of paid vacation
Conference visits and the opportunity to publish relevant discoveries
Free daily meals, drinks, and snacks at our green and modern office in the heart of Berlin
Regular team events and a yearly retreat
Company-sponsored public transport ticket (Deutschlandticket)
Hybrid work model (at least 60% on-site)
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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