Key Skills

Software

Appen

Labelbox

Internal/Proprietary Tooling

Top Subject Matter

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Top Data Types

Geospatial Tiled Imagery

Top Label Types

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Classification

Freelancer Overview

I am an AI engineer and researcher with hands-on experience in building and optimizing AI-driven systems, particularly in the domains of remote sensing and meteorology. My work has focused on developing and applying deep learning models—such as transfer learning and U-Net architectures—for data labeling, annotation, and gap filling in large-scale satellite datasets. I am proficient in Python (PyTorch, Scikit-learn, Xarray), MATLAB, and SQL, and have extensive experience with geospatial data, multi-source data fusion, and the end-to-end preparation of high-quality training data for machine learning applications. I have authored peer-reviewed publications and led technical projects involving spatio-temporal data analysis, ensuring data integrity and accuracy for AI model development. My background also includes mentoring teams on technical best practices and contributing to international research collaborations in computer vision for earth observation

Labeling Experience

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Work History