Etienne David
Senior Agentic AI Engineer at Münchmeyer Petersen Capital Markets
Hamburg, Germany
Summary
👤
Senior🎓
Top SchoolEtienne David is a Senior Agentic AI Engineer based in Hamburg with nine years of experience building production-grade AI systems that bridge research and operations. He architects agentic platforms (MCP servers), RAG pipelines, LLM evaluation frameworks and industrial computer vision stacks, and has a track record deploying models in messy real-world settings from vertical farming to multi-camera quality control. With a PhD in Agricultural Sciences and 2,700+ citations, he uniquely blends deep academic credibility—coordinating large open datasets like the Global Wheat Head Dataset—with hands-on infra work (Metabase-driven data architectures, AWS, PyTorch, OR-TOOLS). A pragmatic founder and former Senior Data Scientist, he translates between technical teams and business stakeholders to turn prototypes into reliable, measurable production outcomes.
9 years of coding experience
8 years of employment as a software developer
Master of Engineering (M.Eng.), Biology/Biological Sciences, General, Master of Engineering (M.Eng.), Biology/Biological Sciences, General at AgroParisTechPreparatory classes to the entrance exams for Grandes Ecoles, BCPST, Preparatory classes to the entrance exams for Grandes Ecoles, BCPST at Lycée Janson-de-SaillyMaster's Degree in Computer Science, Data Mining, Machine Learning, Data Science, Bioinformatics, Master's Degree in Computer Science, Data Mining, Machine Learning, Data Science, Bioinformatics at Université Paris Dauphine - PSLBaccalauréat with distinction, Terminale S (Major in Mathematics, Physics and Biology), Baccalauréat with distinction, Terminale S (Major in Mathematics, Physics and Biology) at Saint Louis de Gonzague-FranklinDoctor of Philosophy - PhD, Plant Sciences, Doctor of Philosophy - PhD, Plant Sciences at Avignon Université
French, English, German, Italian
Stackoverflow
11reputation
640reached
0answers
1question
Github Skills (13)
object-detection10
computer-vision10
machine-learning10
pytorch10
python10
data-set9
metric9
datasets9
evaluation9
faster-rcnn9
object-detection-api6
deep-learning6
tensorflow6
Programming languages (4)
Github contributions (5)
p-lambda/wilds
Mar 2021 - Dec 2021
A machine learning benchmark of in-the-wild distribution shifts, with data loaders, evaluators, and default models.
Role in this project:
ML Engineer
ML EngineerContributions:7 reviews, 29 commits, 4 PRs in 8 months
Contributions summary:Etienne primarily contributed to implementing and refining machine learning models for object detection within the `wilds` repository, which focuses on distribution shifts. Their work included creating a `DetectionAccuracy` metric for evaluating detector performance and integrating it into the GWHD dataset. The commits also show modifications to existing Faster-RCNN implementations and dataset configurations. The user's focus seems to be on enhancing the benchmarking capabilities of the repository.
loadersshiftswildmachine-learningmachine-learning-benchmark
AFDLab4Dev/dataviz-platform-AFD
Oct 2017 - Nov 2017
Contributions:27 commits, 31 pushes, 1 branch in 1 month
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