Senior Engineer, ML/Data

About the role

We are looking for a senior engineer who will shape the data and AI foundation for Danfoss Climate Solutions. You will turn complex sensor, device and business data into reliable, AI‑ready products and production‑grade machine‑learning workflows that drive energy optimisation and predictive insights.

Key responsibilities

• Design, build and maintain scalable data pipelines and ML‑enabled data products, integrating sensor, device, product and business data.
• Develop and improve data ingestion, transformation and orchestration workflows using Airflow, Mage or Dagster.
• Collaborate with data scientists, platform engineers and domain experts to create high‑quality, model‑ready datasets.
• Support deployment, monitoring and operation of machine‑learning solutions in production, including KServe‑based model serving and MLOps workflows.
• Automate data quality checks, feature pipelines, model retraining and deployment to ensure reliable production workflows.
• Contribute to semantic data models and knowledge‑graph capabilities that enrich analytics and AI use cases.
• Continuously improve scalability, observability, reliability and maintainability of the data and ML platform through automation and strong engineering practices.

Required profile

• Strong hands‑on experience in data engineering or machine‑learning engineering with solid Python and SQL skills.
• Experience building and orchestrating production data pipelines using tools such as Airflow, Mage or Dagster.
• Proficiency with cloud platforms (Azure, AWS or GCP) and container technologies like Docker and Kubernetes.
• Good understanding of MLOps, production model deployment and modern data architectures; experience with KServe is a plus.
• Strong problem‑solving and collaboration skills across technical teams and stakeholders.
• Experience with industrial IoT data, HVAC, energy systems, knowledge graphs or semantic data models is advantageous.

Required skills

• Python
• SQL
• Airflow
• Mage
• Dagster
• Azure
• AWS
• GCP
• Docker
• Kubernetes
• KServe