Senior Deep Learning Engineer

Stellenbeschreibung:

At Audatic, we build systems to render speech from any sound scenario clear and free of noise using state-of-the-art deep learning technology. Our mission is to empower millions of people with hearing loss to enjoy interactions in demanding social settings like bars or restaurants.

As a part of the Sonova Group, our team developed the speech enhancement neural network for the Phonak Infinio Sphere - the world’s first hearing aid to run a deep neural network (DNN) for real-time speech enhancement on a custom-built, low-power, embedded neural accelerator. Since then, numerous clinical studies and extensive market feedback have confirmed the significant, life-changing benefits of this breakthrough technology.

As a small, supportive team within a global leader, we pair startup agility with Sonova’s scale, audiological expertise, and world‑class resources. Everyone here has the chance to shape how we work, contribute their ideas and have a direct impact on the products we deliver - creating technology that can transform lives.

Please note that the role outlined below is an on‑site opportunity with a hybrid setup requiring at least 60% office attendance. Fully remote work is not possible. You should ideally be located in Berlin or close enough for an easy commute, or be open to relocating.

About the role

Deep Learning Engineers form the core of our team at Audatic. If you are excited to develop novel algorithms for customizable sound environments, we have a fantastic job opportunity for you!

Your responsibilities will include:

  • 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 and identify new ideas for our project work and research initiatives.
  • Developing and conducting automated hyper‑parameter optimizations on our dedicated GPU cluster and custom deep learning software stack.
  • Taking end‑to‑end ownership of deep learning projects from idea to product deliverable and provide guidance in technical discussions and code reviews.
  • Contributing to learning efforts in the team like our regular journal club, brainstorming sessions, and co‑learning through online courses.

About you

  • Bachelor’s or Master’s degree in a technical field and at least 5 years of relevant experience or a Ph.D. in the field and at least 2 years of relevant experience
  • Strong proficiency in Python with a demonstrated ability to write robust, clean and maintainable code
  • Proven track record of publications or solving real‑world problems with deep learning
  • Dependable communication skills with full professional proficiency in English
  • Experience with digital signal processing or audio processing

What we offer

  • Competitive compensation package
  • 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
  • Hybrid work model (at least 60% on‑site)

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.

We look forward to your application!

Audatic 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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Stelleninformationen

  • Veröffentlichungsdatum:

    11 Mär 2026
  • Standort:

    WorkFromHome
  • Typ:

    Vollzeit
  • Arbeitsmodell:

    Vor Ort
  • Kategorie:

  • Erfahrung:

    2+ years
  • Arbeitsverhältnis:

    Angestellt

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