Machine Learning Engineer

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. 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:

• 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.

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.

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 encourage you to apply Even if you don’t match all the above-mentioned skills, we welcome your application if you think you have transferable skills. 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. How to apply? Use the ‘APPLY’ link no later than August 30th. Applications are assessed continuously, so don’t wait to send yours. Join us in bringing people closer GN brings people closer through our advanced intelligent hearing, audio, video, and gaming solutions. Inspired by people and motivated by innovation, we deliver technology that enhances the senses of hearing and sight. We enable people with hearing loss to overcome real-life problems, improve communication and collaboration for businesses, and provide great experiences for audio and gaming users. We hope you will join us on this journey and look forward to receiving your application.