Machine Learning Engineer

ICEYEMachine Learning Engineer LocationEspooEmployment TypeFull timeLocation TypeHybridDepartmentSolutionsRole highlights:Machine Learning EngineerLocation: Espoo, Finland. Relocation to Finland requiredDepartment: Product EngineeringReports to: Geospatial Machine Learning Team LeadEmployment type: PermanentWorkplace model: HybridEmployment is subject to applicable security screening (incl. SUPO, where required)Why this role matters: As a Machine Learning Engineer, you’ll turn Earth Observation data into intelligence that helps governments, insurers, and emergency responders make faster, better decisions. You'll build and deploy ML systems that sit at the core of ICEYE's products, with direct impact on what customers can see and act on at global scale. Working in a cross-functional team alongside domain experts, product managers, and software engineers, you'll contribute across the full ML lifecycle, from data pipelines and model development through to deployment and continuous improvement. Who We AreICEYE is the world leader in sovereign intelligence from space. We deliver persistent monitoring capabilities to detect and respond to changes in any location on Earth. ICEYE owns the world's largest and most advanced SAR (synthetic aperture radar) satellite constellation. To our customers we provide intelligence with unmatched quality, latency and revisit times, in any weather, day or night. To governments who choose to operate their own constellation we provide this proven capability as a sovereign system. ICEYE-built constellations serve customers in defence and intelligence, environmental monitoring, insurance and emergency management. We enable fast decisions that contribute to a safer future. Founded and headquartered in Finland, ICEYE operates globally with over 1000 employees across Europe, North America, the Middle East, and Asia-Pacific.Your day-to-day responsibilities Design, develop, and deploy machine learning models and services for Earth Observation applicationsContribute to the development, fine-tuning, evaluation, and operationalization of foundation models and large-scale representation learning approachesBuild and maintain scalable ML pipelines for data preparation, training, validation, and inferenceWork with large-scale Earth Observation datasets, including SAR, optical, and multi-modal sourcesCollaborate with domain experts and product teams to translate business and customer needs into ML solutionsImprove model performance, reliability, and operational efficiency through rigorous evaluation and monitoringContribute to reusable ML infrastructure, tooling, and shared best practices within the teamSupport experimentation and rapid prototyping for new productMaintain existing production and deployed systemsContribute to platform and product development efforts, supporting the integration of ML systems into broader engineering and customer-facing products What we’re looking forMust haves:MSc or PhD in Computer Science, Machine Learning, Remote Sensing, Data Science, or a related field, or equivalent practical experienceSolid experience developing machine learning models using modern frameworks such as PyTorch or TensorFlowExperience with foundation models, self-supervised learning, representation learning, or large-scale deep learning systemsExperience deploying and maintaining machine learning models in production environmentsStrong software engineering skills in Python and familiarity with modern software development practicesSolid understanding of model evaluation, validation, reproducibility, and performance monitoringExperience building reliable data and ML pipelines Nice to haves:Experience with Earth Observation data (SAR, optical, or multi-modal)Familiarity with foundation models for Earth Observation or geospatial applicationsExperience with MLOps, CI/CD, model registries, and cloud-based ML platformsKnowledge of geospatial data formats and large-scale data processing frameworksExperience with...