LoOp builds Artificial Intelligence that plans delivery routes for retailers, wholesalers and carriers across Denmark and Europe — cutting fuel, cost and CO₂ on every route. Our models run in production every day for 6+ customers, and we are now scaling the platform behind them.
The role
As our first dedicated MLOps Engineer, you will own the path from model to production. You will work directly with the founders and our ML team to make sure the models that plan thousands of stops a day are trained, deployed, monitored and improved reliably. This is a hands-on role with real ownership and a direct line to customers.
Your responsibilities
- Design and run the pipelines that train, evaluate and deploy our routing and forecasting models.
- Build and maintain CI/CD, model registry and feature store infrastructure.
- Set up monitoring for model performance, data drift, latency and cost.
- Keep production services fast and available for customers running daily fleets.
- Work with engineers and researchers to move experiments into production quickly and safely.
Your profile
- 3+ years of experience running machine learning or data systems in production.
- Strong Python, plus Docker and Kubernetes.
- Experience with MLflow, Kubeflow, Airflow or similar tools.
- Hands-on with at least one major cloud (AWS, GCP or Azure) and infrastructure as code.
- You take ownership, communicate clearly and like solving problems end to end.
- Fluent English. Danish is a plus.
What we offer
- A key role in an early-stage company with real customers and a clear mission.
- Direct impact on the product and the technical direction from day one.
- Hybrid work from Aarhus with flexible hours.
- Competitive salary and the opportunity for equity.
- A small, ambitious team that values curiosity and good engineering.
How to apply
Send your CV and cover letter using the form below. We review applications continuously, so apply as soon as possible. For questions about the role, write to ali@thelooploop.com.