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Deep Learning Engineer — Satellite Image Classification

Min-Ji Park

Contract · Senior

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About the role

We're building a land-use change detection system using multispectral Sentinel-2 imagery at global scale. We need to classify land use across 6 categories (forest, cropland, urban, water, grassland, bare soil) and detect changes between time periods. Current approach is a U-Net variant — working but underperforming on cloud-contaminated images and class boundaries. We need someone to improve the architecture and training pipeline, handle missing-data imputation for cloudy pixels, and scale inference to continental coverage. Expected output: improved model, training pipeline, and an inference service that can process a full country in under 24 hours on our cloud setup.

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Categories

Computer Vision & Deep Learning AI & Machine Learning Engineers computer vision

Skills

computer vision pytorch python tensorflow

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Contract Type

Hourly rate

Level

Senior

Budget Range

$85 – $125 / hour

Duration

5 months

AI Expertise

Computer Vision & Deep Learning AI & Machine Learning Engineers computer vision

Skills

computer vision pytorch python tensorflow

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