METRICSAT is an early-stage Luxembourg-based company developing an environmental data and analytics platform to help financial institutions assess and report on their investment portfolios' environmental risks and impacts.

We're now growing our technical team to accelerate product development and are looking for a highly skilled Lead Geospatial Machine Learning Operations (MLOps) Engineer to join us on-site in Luxembourg.

What You’ll Do

As a Lead Geospatial MLOps Engineer, you’ll lead the development and deployment of automated, scalable ML, cloud-based pipelines from model development through deployment and retraining, tailored specifically for physical environment use cases.

Key Responsibilities

• Train, evaluate, and optimize ML models for physical environment use cases
• Build and deploy reliable model serving architectures (batch, API, or streaming-based).
• Leverage cloud platforms (e.g., AWS, GCP) and orchestrators (e.g., Airflow, Prefect) to scale across global datasets.
• Ensure robust versioning of models
• Collaborate with scientists to translate environmental models into operational pipelines.

Candidate Profile

• 4+ years of experience in MLOps with a geospatial focus.
• Strong proficiency with Python and libraries like Rasterio, GDAL, NumPy, scikit-learn, PyTorch/TensorFlow.
• Experience with remote sensing workflows and geospatial data formats (GeoTIFF, NetCDF, shapefiles).
• Familiarity with cloud-native tools (AWS S3/EC2/SageMaker, GCP Earth Engine, etc.).
• Experience deploying ML models using Docker, FastAPI, or similar frameworks.
• Knowledge of spatiotemporal data modeling or environmental monitoring applications.
• Bonus: background in climate science, hydrology, agriculture, or urban systems.

What We Offer

• Take ownership and help shape a one-of-a-kind product,
• Work with the latest technologies,
• Contribute to the deployment of first-of-its-kind solutions.
• Full-time employment contract