(Senior) Machine Learning Engineer

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WS Audiology

Formed in 2019, through the merger of Sivantos and Widex, WS Audiology combines over 140 years’ experience in pioneering the use of technology to help people with hearing loss hear the sounds that make life wonderful. We are active in over 125 markets and employ 11,000 people worldwide. Our broad portfolio of hearing related products and services generates annual revenues of around EUR 1.7 billion.

Learn about us on www.wsa.com

The Team

To deliver on our purpose to make wonderful sound part of everyone’s life, we are strengthening our capabilities with an additional, passionate and purpose-driven team player in our AI Accelerator team.

This team is a newly established, self-driven unit, reporting directly to our Chief Research Officer, with the purpose of challenging status quo in audiology and hearing-aid business through innovations using data-driven approaches. 

The team will be fast paced and therefore needs to constantly be on the forefront of the newest technologies and principles. The team focus will be to develop fully functional prototypes crammed with innovations and novelty and the team is staffed with the people that delivered e.g. the award-winning SoundSense Learn technology.

You will be located in our CO2 neutral headquarters north of Copenhagen with dynamic and progressive colleagues, who are highly skilled and empathic   . You will work hard and play hard together, and you will do this because you are eager to make a difference and to learn and challenge yourself. We are still adjusting to "new work environment" post covid-19 and therefore encourage any applicant to have an open discussion about how the best setup would  look like for you, in this role.

The Role

As Machine Learning Engineer, you will develop end-to-end models driving the next leap within audio processing and audio synthesis. You will be working in teams together with other ML engineers, as well as cloud and software developers, building prototypes that demonstrate business applications.

In this role you will have the following responsibilities:

  • Apply the most recent methods and advances within the ML community (e.g., from NeurIPS, ICML, ICLR etc.) 
  • Ensure that you and the team is always on the forefront of ML methodologies and principles.   
  • Successfully adapt and advance ML models and principles to the audio domain.
  • Support and embrace the use of modern DevOps and MLOps principles in your daily work.
Your profile 

We are looking for a highly experienced machine learning engineer, that is not afraid of deriving math with pen and paper, and as importantly, the modern software platforms for making scalable AI modeling. You know that data is your gold, but you will never have enough. 

Therefore, you need to be clever with your data but also pursue other ways than just to have more of it. You know that if you are too naïve, compute cost will come back to haunt you. It is therefore expected by you, to have a deep understanding of the pros and cons of different machine learning models and the impact of the domain. As the rest of the group, you know that understanding comes by both reading and hands on development as well as hacking

Additionally, you are a strong communicator that knows when to insist and when to accept a compromise. You are a team player, who seeks design feedback and engage in constructive discussions with your fellow colleagues, who like you cherish openness, constructive feedback and constant professional development. Creativity, attention to detail, and a collaborative attitude are part of your strengths.

  • Master’s degree in computer science or a similar field
  • Experience with public cloud platforms (e.g., AWS, Azure, GCP, etc.)
  • Experience with machine learning platforms (e.g., TensorFlow/Keras, PyTorch , scikit-learn, JAX, etc.)
  • Knowledge of deep learning approaches in general (e.g. transformers, variationally autoencoders, generative adversarial networks, etc.)
  • Extensive experience with audio deep learning approaches (e.g., dilated convolutional neural networks, autoregressive generative models)
You as a person
  • You are curious about new technologies and open-source community
  • You cherish cloud-native
  • You will be comfortable with handling multiple tasks simultaneously
  • You can work independently and have excellent problem-solving skills

The corporate language is English, so you need to be fluent in English, both verbally and in writing.

Join WS Audiology

Please submit your CV as soon as possible. We will screen and invite candidates for interviews on an ongoing basis.

We usually respond within two weeks

Or, know someone who would be a perfect fit? Let them know!

Lynge / Greater Copenhagen Area

Nymøllevej 6
3540 Lynge Directions

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