🔹Title: Machine Learning Engineer
🔹Location: Espoo, Hybrid
🔹Type of Contract: Permanent
🔹Team: Geospatial Machine Learning

About ICEYE

ICEYE is the global leader in synthetic aperture radar (SAR) satellite operations for Earth Observation, persistent monitoring, and natural catastrophe solutions; owning and operating the worlds largest SAR constellation. ICEYE is headquartered in Finland and operates from five international locations with more than 600 employees from nearly 60 countries, inspired by the shared vision of improving life on Earth by becoming the global source of truth in Earth Observation.

Our satellites acquire images of Earth at any time – even when it’s cloudy or dark – providing commercial and government partners with unmatched persistent monitoring capabilities. Information derived from our SAR images helps customers make data-driven decisions to address time-critical challenges in various sectors, such as maritime, disaster management, insurance, and finance.

Our team is a tight-knit group of experts across many disciplines (e.g., engineering, software development, radar technology, etc.). We’re innovative, driven people who strive for excellence in everything we do. Teamwork, curiosity, and having fun are core values at ICEYE, and contribute to Making the Impossible possible!

About the Role

We are looking for a motivated and technically skilled specialist to join our Machine learning team to work on automated change detection from satellite imagery. You will contribute to the design, development, and deployment of models and pipelines that identify meaningful changes on the Earths surface over time (e.g., building damages, deforestation, urban expansion, infrastructure monitoring, etc.) using multi-temporal SAR data and/or optical.

At ICEYE, We work in cross-functional product teams, bringing together domain experts in Earth observation, machine learning engineers, product managers, and software engineers. from understanding user needs to deploying scalable solutions. Our machine learning team supports this by building the tools, infrastructure, and reusable components that enable fast iteration and experimentation across products. We foster a collaborative environment where sharing knowledge and improving together is part of our daily routine.

Responsibilities

Design, implement, and evaluate change detection algorithms using EO data (optical, SAR, multi-sensor).
Develop and optimize pipelines for data preprocessing, co-registration, and time-series analysis.
Train and validate models for detecting and classifying changes.
Work with large EO datasets (e.g., Sentinel-1/2, ICEYE) and manage them efficiently.
Collaborate with domain experts to translate real-world monitoring needs into algorithmic solutions.

MSc or PhD in Remote Sensing, Geoinformatics, Computer Science, Earth Sciences, or related fields.
Strong experience in EO image processing (e.g., radiometric calibration, co-registration, time-series analysis).
Proficiency with Python and ML libraries (e.g., Rasterio, GDAL, OpenCV, scikit-learn, PyTorch/TensorFlow, HuggingFace).
Solid understanding of model evaluation and model deployment
Experience writing unit tests, validating pipelines, and ensuring reproducibility in ML/EO workflows.
Hands-on experience with change detection techniques (proven records)
Knowledge of geospatial formats and cloud-based EO data access (e.g., AWS, STAC, xarray).

Nice-to-Have

Experience with near real-time EO applications or operational monitoring systems.
Familiarity with MLOps or deployment on cloud infrastructure.
Familiarity with SAR data (e.g., Sentinel-1, ICEYE)
Familiar with EO embeddings at large scale