I

Machine Learning Engineer

icon building Company : Iceye
icon briefcase Job Type : Full Time

Number of Applicants

 : 

000+

Click to reveal the number of candidates who applied for this job.
icon loader
icon loader

Let AI Supercharge Your Job Hunt!

JobCopilot scans 500,000+ company career sites daily to find jobs for you

Never miss an opportunity Save hours by auto-filling applications forms Land more interviews with tailored applications
happy man
thunder iconActivate JobCopilot

Job Description - Machine Learning Engineer

🔹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 world's 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 Earth's 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
  • A job that matters in a dynamic Earth Observation environment with a scale-up approach
  • An independent role with a supportive and diverse work environment
  • Occupational healthcare and accident insurance
  • A yearly benefit budget to spend as you wish (i.e. on sport, transport, bike benefit, wellness, lunch, etc.)
  • Phone subscription with iPhone of your choice 
  • Relocation support if needed (i.e. flight tickets, accommodation, relocation agency support)
  • Time for self-development, research, training, conferences, or certification schemes
  • Inspiring and collaborating offices and silent workspaces enable you to focus
  • A wide variety of the best coffee, tea, snacks, and sweets to accompany your daily space mission

At ICEYE, we believe that diversity isn't just a buzzword – it's our greatest asset. 

We're committed to fostering an inclusive environment where every voice is not only heard but celebrated. We know that diverse perspectives breed innovation and creativity, which is why we actively seek out individuals from all walks of life, backgrounds, and experiences. 

Whatever your background, we want you to bring your authentic self to the table. Join us and be part of a team where differences are not only embraced but cherished, because together, we're stronger.

Original job Machine Learning Engineer posted on GrabJobs ©. To flag any issues with this job please use the Report Job button on GrabJobs.
Share Job
Share Job

Auto-Apply to Machine Learning Engineer Jobs with your AI JobCopilot

thunder icon Auto-Apply with AI

Similar Machine Learning Engineer Jobs in Finland

GrabJobs is the no1 job portal in Finland, connecting you to thousands of jobs fast! Find the best jobs in Finland, apply in 1 click and get a job today!

Mobile Apps

Copyright © 2026 Grabjobs Pte.Ltd. All Rights Reserved.