Machine Learning Engineer

Location: Ballerup, Denmark; flexible hybrid work with in-person collaboration when needed

Company

hirify.global develops intelligent hearing, audio, video, and gaming solutions that enhance hearing, sight, communication, collaboration, and user experiences.

What you will do

• Explore real-world product data, identify useful features, and assess which advanced ML problems the data can support.
• Build and evaluate classical machine learning and deep learning models using Python and modern ML frameworks.
• Move models from experimentation through deployment, including the data infrastructure and pipelines required for production.
• Evaluate model performance on real-world data and improve reliability after deployment.
• Collaborate with ML architecture, software engineering, and data science colleagues to turn experiments into maintainable product capabilities.
• Use AI-assisted development tools for experimentation and engineering while critically assessing their outputs.

Requirements

• Relevant experience in applied machine learning, including deploying models and improving them in production.
• Practical experience with classical machine learning and deep learning on real-world data.
• Ability to write maintainable Python and work with data quality, model behavior, and production constraints.
• Ability to desihirify.global useful experiments, evaluate results critically, and explain model capabilities and limitations.
• Initiative in exploring open-ended problems and moving work forward independently within an established technical direction.
• Experience with Azure ML, Databricks, Azure DevOps, scikit-learn, TensorFlow, or PyTorch.

Nice to have

• Experience fine-tuning language models on domain-specific data.
• Experience working with regulated products.

Culture & Benefits

• Flexible work is encouraged, with in-person collaboration when it is most effective or needed.
• Work in a relatively new machine learning team within Engineering Excellence.
• Collaborate across hirify.global with colleagues in ML architecture, software engineering, data science, and product engineering.
• Inclusive recruitment process with equal consideration for all applicants.

Hiring process

• Applications are assessed continuously.
• Applicants may inform the Hiring Manager about special interview requirements after accepting an interview invitation.