Machine Learning Engineer
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Machine Learning Engineer
Location
Espoo
Experience
Mid
Posted
Jul 7, 2026
Apply by
August 6, 2026
Applicants
0
Early applicantFull-timeHybrid
Job Description
## **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 geospatial data formats and large-scale data processing frameworks
- Experience with distributed training and large-scale model optimization
- Experience with near real-time or operational monitoring systems
## **Application Process**
- Recruiter screening
- Hiring manager interview
- Technical task
- Technical panel interview
- Final interview
## **Working at ICEYE**
At ICEYE, you’ll join a diverse and highly engaged team united by the ambition to make the impossible possible. As a global scale-up, we combine speed and ambition with the opportunity to take real ownership from day one. Your growth, wellbeing, and success are a priority, with continuous professional development, training opportunities, and a culture where collaboration is how we win.
## **How We Work (Our Values)**
**Make the impossible possible**: We set ambitious goals and stay calm under pressure. We bring grit, optimism, and ownership when things get hard, and we keep moving until we find a way.
- **Be curious**: Go deep, ask questions, listen carefully, and think critically. Understand the “why” behind decisions.
- **See the big picture:** Stay close to what’s happening across the company so you can make better decisions. Consider how your work affects others.
- **Drive effective teamwork:** Create psychological safety, invite different perspectives, and build inclusive teams. There are no bad questions.
- **Act as one team:** We win together. We match tasks to the right owner and stay agile as priorities shift.
- **Have fun**: What we do matters—and it should be enjoyable. Celebrate progress, take pride in results, and share the wins.
## **Benefits**
Our benefits are designed to support your health and wellbeing, at work and beyond. We keep improving them based on employee feedback, and offerings vary by location. Talent Acquisition will confirm what applies for this role and location during the process.
## **Our Commitment to Diversity, Equity, and Inclusion**
We want ICEYE to be a place where people can be themselves and do great work. Different backgrounds and perspectives make us stronger, which is why we work to create an environment where people feel included, respected, and able to speak up. Whatever your background, we want you to bring your authentic self to the table.
We’re committed to fair, inclusive hiring and equal opportunity. Everyone is welcome to apply. If you need any adjustments or support during the recruitment process, tell us—we’ll do our best to help.
Apply now to start your ICEYE journey, and help us continue to make the impossible possible together. Read more about ICEYE and working with us athttp://iceye.com.
Key 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
Requirements
- MSc or PhD in Computer Science
- Machine Learning
- Remote Sensing
- Data Science
- or a related field
- or equivalent practical experience
Skills Required
PyTorchTensorFlowPythonMachine LearningDeep LearningFoundation ModelsSelf-supervised LearningRepresentation LearningModel EvaluationModel ValidationReproducibilityPerformance MonitoringData PipelinesML PipelinesCollaborationCommunicationProblem SolvingCritical ThinkingEarth Observation dataSAROptical dataMulti-modal dataFoundation models for Earth ObservationGeospatial applicationsMLOpsCI/CDModel registriesCloud-based ML platformsGeospatial data formatsLarge-scale data processing frameworksDistributed trainingLarge-scale model optimizationNear real-time monitoring systems
Benefits
- Continuous professional development
- Training opportunities
- Health and wellbeing support
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