MACHINE LEARNING ENGINEER

• Design, develop, test, deploy and monitor end-to-end pipelines for machine learning models in Azure.
• Apply MLOps best practices, including version control, continuous integration, continuous delivery, continuous training, testing, and monitoring, to ensure the quality and reliability of the machine learning solutions.
• Monitor model performance and help identify issues related to model quality, drift, and reliability.
• Support automation of model training, deployment, and retraining processes.
• Contribute to best practices for machine learning engineering, testing, documentation, and deployment.
• Work with Data Engineering and IT teams to ensure solutions are scalable, secure, and reliable.
• Help develop and improve CI/CD processes for machine learning applications.
• Participate in troubleshooting and resolving issues in production ML systems.
• Stay up to date with developments in machine learning, MLOps, and cloud technologies.

• Master's Degree in Computer Science, Engineering, Machine Learning, Mathematics, or a related field.
• 2-5 years of experience in Machine Learning Engineering, MLOps, or a related role.
• Experience developing, deploying, and operating machine learning solutions in production environments.
• Hands-on experience with Azure ML, Azure Databricks, Azure Data Factory, or similar cloud-based ML platforms.
• Proficiency in Python, SQL, Git, and Bash.
• Experience deploying and serving machine learning models through APIs, as well as monitoring model performance in production.
• Understanding of model evaluation techniques, hyperparameter tuning, and validation approaches such as back-testing.
• Familiarity with Infrastructure as Code, preferably Terraform on Azure.
• Solid understanding of software engineering practices, including testing, version control, and CI/CD principles.
• Strong communication skills and the ability to explain and document technical concepts clearly and effectively.
• Experience with Generative AI, LLMs, or AI agents is considered a plus.

We believe you are a curious and pragmatic engineer who enjoys solving problems with data and machine learning. You are comfortable working across the ML lifecycle, from experimentation to production, and enjoy collaborating with colleagues from different disciplines. You are eager to learn, improve your technical skills, and contribute to building reliable AI solutions that create real business value. Most importantly, you understand that successful machine learning is not only about models, but about delivering solutions that work in the real world and continue to provide value over time.

• Apply by November 16, 2026. We review applications continuously and encourage you to apply early, as the position may be filled before the closing date. Please note that, due to GDPR regulations, we cannot accept applications via email.
• This is a full-time position (100%) based at our headquarters in Frösundavik, Solna, Stockholm. We value in-person collaboration, although flexible working arrangements may be available depending on team and business needs.
• As this role contributes to security-classified systems and business-critical capabilities, a background check will be conducted as part of the final stage of the recruitment process.