Machine Learning Engineer

Job Description Build models on real-world product data and bring them into production In the role of Machine Learning Engineer in the Engineering Excellence team within Software Solutions. You will work on applied machine learning for GN's products, contributing across the model lifecycle, from exploring data and evaluating approaches to deployment and ongoing improvement. You will explore advanced machine learning use cases and turn promising ideas into reliable capabilities for GN’s products. This is an opportunity to work at the forefront of applied ML, where you will help investigate new possibilities, challenge established approaches, and contribute to creating the foundations for how the team works and delivers.

Team The Team you will be part of: Based in Ballerup near Copenhagen, Engineering Excellence works with engineering teams across GN to build quality software capabilities for our products. You will join a relatively new machine learning team, collaborating with colleagues who bring expertise in ML architecture, software engineering and data science. Together, we explore use cases using real-world product data, where understanding data quality, limitations, and useful signals is essential to building reliable models and product capabilities. Your contribution is appreciated, and you will:

Responsibilities Explore real-world product data, identify useful features and assess which advanced problems the available data can support.

Build and evaluate classical machine learning and deep learning models, testing new approaches where they can create product value.

Take models from experimentation through deployment, contributing to the data infrastructure and pipelines they need.

Assess model performance on real-world data and improve reliability in production.

Work in Python with Azure ML, Databricks and Azure DevOps, using tools such as scikit-learn, TensorFlow or PyTorch.

Use AI-assisted development tools to support experimentation and engineering, applying sound judgement to their outputs.

Collaborate with colleagues to turn experimental results into maintainable product capabilities and help shape effective ways of working as the team grows.

Requirements To perform well in the role, we imagine that you: Bring relevant experience in applied machine learning, including taking models from experimentation through deployment and improving them in production. Have practical experience with classical machine learning and deep learning on real-world data, and write maintainable Python. Take initiative in exploring open-ended problems, designing useful experiments and moving work forward independently within an established technical direction. Can design useful experiments, evaluate results critically and explain what a model can and cannot do. Are curious about emerging ML technologies, data, model behaviour and product needs, and can evaluate results critically to explain what a model can and cannot do. Focus on delivering reliable outcomes, seek input when helpful, and constructively challenge assumptions and approaches to improve the solution. Experience fine-tuning language models on domain-specific data is an add-on, as is experience working with regulated products.

Culture & Perks At GN we pride ourselves on encouraging flexible work whenever possible. We trust our people to fulfill their responsibilities, to know when in-person collaboration is better than hybrid, and to be present when it's needed most.

We highly value a mindset and motivation that align with our core values, to not only ensure growth for you, but for your team and the wider GN organization as well.

We are focused on an inclusive recruitment process. All applicants will receive equal consideration for employment. As such, we encourage you to submit your CV without a photo to ensure an equal and fair application process. Should you have any special requirements for the interview, please let the Hiring Manager know upon accepting the invitation to the interview.

About Jabra and GN Group #LI-Jabra Jabra is a leading brand in engineering communications and sound solutions – innovating to empower both consumers and businesses. Our engineering excellence allows us to create integrated headsets and communications tools that help professionals work more productively; wireless headphones and earbuds that let consumers better enjoy calls, music, and media; and pioneering video conferencing solutions which offer wall-to-wall coverage with no distortion. Jabra is part of the GN Group which was founded with a truly innovative and global mindset. Today, we honor that legacy with world-leading expertise in the human ear, sound, wireless technology, miniaturization and collaborations with leading technology partners. GN's solutions are marketed by the brands ReSound, Beltone, Interton, Jabra and BlueParrott in 100 countries. Founded in 1869, the GN Group employs 6,000 people and is listed on Nasdaq Copenhagen (GN.CO). If you would like to learn more about our brand, please click on the link to explore our universe of sound.

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