🔹Title: SAR Scientist🔹Location: Valencia, Spain preferred | Espoo, Finland | Athens, Greece | Warsaw, Poland🔹Type of Contract: Permanent🔹Team: SAR Analytics Team🔹 Hybrid (3-days a week onsite) About ICEYEICEYE 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 700 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! What are we looking for?Are you driven to push the boundaries of whats possible with SAR data and machine learning? We are seeking an innovative SAR Scientist to join our SAR Analytics team, reporting to the Team Lead. While working closely with our Geospatial Machine Learning team, your mission will be to serve as the subject matter expert on applying advanced signal processing and machine learning specifically to the unique challenges and opportunities of SAR data. This role is vital for our long-term mission to drive business growth by turning deep science into new product capabilities.Looking to the future, this role will also be pivotal in developing multi-modal solutions that fuse our core SAR data with optical and RF sensor feeds, creating a new frontier of analytical products.<h3>Who You Are:</h3><ul> <li>You are deeply curious about the “why” behind the data and passionate about exploring novel approaches to complex problems.</li> <li>You are a creative and inventive thinker, comfortable with ambiguity and excited by the prospect of exploring uncharted territory.</li> <li>You continuously track the latest industry and academic breakthroughs, identifying opportunities to create a competitive advantage.</li> <li>You are a self-starter who can independently drive a project from initial concept to a validated prototype that demonstrates clear business value.</li> </ul><h3>Your Responsibilities:</h3><ul> <li>Design, build, prototype, and maintain state-of-the-art algorithms and machine learning models (focus on deep learning) for SAR data analysis.</li> <li>Lead strategic initiatives to unlock the full potential of SAR-specific information (e.g., interferometry, polarimetry, coherence) for applications like automated change detection and object classification.</li> <li>Pioneer novel data fusion techniques, combining SAR with optical, RF, and other data sources to create information products that are more than the sum of their parts.</li> <li>Translate the latest advancements in machine learning and remote sensing into tangible business opportunities and new product capabilities.</li> <li>Collaborate closely with remote sensing and software engineers to transition successful prototypes into robust, operational pipelines.</li> </ul>Employment is subject to applicable security screening (incl. SUPO, where required)<ul><li>Ph.D. (preferred) or Masters degree in Computer Science, Electrical Engineering, Telecommunication Engineering, Remote Sensing, or a related field.</li></ul><ul> <li>Proven experience in applying machine learning to complex data problems, preferably with geospatial, remote sensing, or image data.</li> <li>Deep understanding of SAR phenomenology and its information content (e.g., coherence, amplitude, phase, polarimetry) is required.</li> <li>Theoretical and practical expertise in machine learning, including deep learning (e.g., CNNs, Transformers, Self-Supervised Learning) and classical ML techniques.</li> <li>Strong programming skills in Python and proficiency with ML frameworks such as PyTorch or TensorFlow, and libraries like Scikit-learn.</li> <li>Proficiency with version control systems, particularly Git, and a commitment to high-quality, reproducible work.</li> </ul><ul><li>Commitment to engineering best practices (e.g., code reviews, testing, documentation) to work seamlessly with data and software engineers to build operational solutions.</li></ul><ul><li>Excellent communication skills, with the ability to articulate complex technical concepts to both specialist and non-specialist audiences.</li></ul><h3>Valuable Skills (Nice to Have):</h3><ul> <li>Experience with multi-modal data fusion (e.g., SAR-optical fusion).</li> <li>A background in signal processing, particularly as it relates to radar or SAR systems.</li> <li>Experience with large-scale data processing frameworks (e.g., Dask, Spark).</li> <li>Familiarity with MLOps principles and tools for deploying and managing machine learning models in production.</li> </ul><ul><li>Experience working in an Agile/Scrum development environment.</li></ul><ul><li>Familiarity with cloud computing environments (e.g., AWS) and containerization technologies (Docker).</li></ul>