Job Opportunities API

ROLE HIGHLIGHTS: - Machine Learning Engineer - Location: Espoo, Finland. Relocation to Finland required - Department: Product Engineering - Reports to: Geospatial Machine Learning Team Lead - Employment type: Permanent - Workplace model: Hybrid - Employment 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 ARE ICEYE 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 applications - Contribute to the development, fine-tuning, evaluation, and operationalization of foundation models and large-scale representation learning approaches - Build and maintain scalable ML pipelines for data preparation, training, validation, and inference - Work with large-scale Earth Observation datasets, including SAR, optical, and multi-modal sources - Collaborate with domain experts and product teams to translate business and customer needs into ML solutions - Improve model performance, reliability, and operational efficiency through rigorous evaluation and monitoring - Contribute to reusable ML infrastructure, tooling, and shared best practices within the team - Support experimentation and rapid prototyping for new product - Maintain existing production and deployed systems - Contribute to platform and product development efforts, supporting the integration of ML systems into broader engineering and customer-facing products   WHAT WE’RE LOOKING FOR Must haves: - MSc or PhD in Computer Science, Machine Learning, Remote Sensing, Data Science, or a related field, or equivalent practical experience - Solid experience developing machine learning models using modern frameworks such as PyTorch or TensorFlow - Experience with foundation models, self-supervised learning, representation learning, or large-scale deep learning systems - Experience deploying and maintaining machine learning models in production environments - Strong software engineering skills in Python and familiarity with modern software development practices - Solid understanding of model evaluation, validation, reproducibility, and performance monitoring - Experience 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 applications - Experience with MLOps, CI/CD, model registries, and cloud-based ML platforms - Knowledge of