Etienne Landuré is an R&D engineer with eight years’ experience building production-grade software and deep learning pipelines, currently based in Santiago, Chile. Trained at ENIB, he has applied his generalist engineering background to medical imaging—designing an asynchronously distributed pre-segmentation platform and end-to-end tools for training, validating and deploying neural networks at Visible Patient Lab. His early roles at CNES and Atos show a rare mix of space-standard systems engineering (Go, CCSDS/MAL) and applied deep learning (CNNs, U-Net family) for segmentation tasks, bridging rigorous research methodology with product delivery. Comfortable across Python, C++, Go and tooling for testing and quality management, he also builds internal automation—from anomaly detection in documents to automated UI test execution—that improves operational reliability. Notably, he has experience shipping both domain-specific R&D prototypes and robust internal services that scale beyond single projects.
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Etienne Landuré - R&D Engineer at Visible Patient Lab