Freelancer profile translated to English.
Back to original languageAbout Agnès
About Me
I am a Lead ML Engineer specializing in Computer Vision | Data Scientist | +15 years of experience | YOLO, RAG & LLM, Transformers, AWS Cloud.
From scattered data and manual analyses, I design industrialized Vision & AI solutions that drive decision-making.
With over 15 years of experience in structuring complex topics and strategic & budget management, I translate business challenges into robust ML architectures to move from experimentation to real-world industrialization.
Why Me?
My strength lies in the hybridization of 3 pillars:
1️⃣ Tech Expertise: Mastery of the complete cycle (Data Science, Computer Vision, MLOps & Cloud).
2️⃣ Decision-Making: Macroeconomic vision and budget management inherited from my management roles.
3️⃣ Communication Skills: Ability to simplify abstract concepts to unite stakeholders, from the field to the board.
My Areas of Expertise
✅ Computer Vision & Industrialization: Automation of object detection and segmentation (YOLO) on AWS, transforming laborious manual calculations into high-performance production workflows.
✅ Generative AI (RAG/LLM): Design of intelligent extraction systems to structure massive volumes of unstructured data and boost R&D productivity.
✅ Modeling & Accuracy: Development and optimization of Machine Learning / Deep Learning models on spectral and genotypic data, securing strategic decision-making.
How We Work Together
- Based in Bordeaux.
- Remote interventions.
- Available immediately, full-time.
- Response via Malt within 2 hours.
French
Native or bilingual
English
Conversational
Remote only
Primarily works remotely
Experience
- Mas Seeds groupe MaïsadourData Scientist / Machine Learning EngineerRAW MATERIALS INDUSTRYSeptember 2024 - February 2026 (1 year and 5 months)Bordeaux, FranceThe challenge:From a fragmented and partially manual approach to automated, innovative, and competitive R&D thanks to ML models and advanced analysis tools.My mission was to modernize analysis tools and leverage existing data to improve variety selection, accelerate R&D, automate processes, and innovate in variety creation, in line with business objectives.I intervened in 5 areas:1️⃣ Identification and optimization of higher-performing ML/DL models on multi-trait NIRS data, to improve corn composition prediction and secure the selection of better varieties.2️⃣ Implementation of an automated data extraction system from PDFs (RAG + LLM) to save time and improve R&D productivity.3️⃣ Development of a RandomForest model to classify sunflower genotypic data and improve the reliability of qualitative variety creation.4️⃣ Testing and evaluation of an innovative Transformer model specialized in genomic data to identify genes of interest and improve variety selection methods.5️⃣ Object detection and segmentation on images (corn ears and kernels), with industrialization on AWS, to improve the reliability and speed of yield and productivity calculations.Results:✅ 18% reduction in average error on NIRS models, improving the reliability of variety selection decisions.✅ Automation of PDF extractions, generating significant productivity gains for R&D.✅ RandomForest classification and genotypic data analysis, optimizing the description of genetic diversity and the creation of new varieties.✅ Acceleration and improved reliability of yield and productivity calculations thanks to Computer Vision.✅ Overall contribution to faster, more reliable, and competitive R&D, strengthening customer confidence and innovation capacity against competition.
- Openclassrooms –CentraleSupélecProfessional BreakEDUCATION AND E-LEARNINGSeptember 2022 - August 2024 (1 year and 11 months)Bordeaux, FranceIn training with Openclassrooms:
- Seven applied projects on business cases (banking, retail, energy, health) validated in defense.
- ML & DL in Python, Deployment/MLOps: API, dashboards, AWS, PySpark, Computer Vision.
Python, Deep Learning, NLP, CNN, scikit-learn, TensorFlow, AWS, Streamlit, Flask - Education NationaleStrategic and Resource Management (Assistant School Principal)PUBLIC SECTORSeptember 2020 - August 2022 (1 year and 11 months)Bordeaux, FranceMy management experience allows me to approach an ML project not only from a technical perspective but also from a budgetary, organizational, and political standpoint:1️⃣ Complex Project Management: Steering pedagogical policy and coordinating multidisciplinary teams.2️⃣ Innovation Management: Implementing digital solutions and optimizing material/budgetary resources.3️⃣ HR Management: Leading multidisciplinary teams, conflict resolution, and change management.4️⃣ Strategic Steering:⠀⠀✅ Organization and continuity of service: HR planning, contingency management, and communication steering.⠀⠀✅ Implementation of pedagogical policy.⠀⠀✅ Budget construction and management under an objectives contract with the relevant territorial authority, respecting 7 fundamental principles including balance and sincerity.
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Education
- Machine Learning EngineerOpenclassrooms2026Huit projets appliqués sur des cas métier multi-disciplinaires, évalués en soutenance : - Analyse de données sur l’alimentation, - Catégorisation de données textuelles et image, - Segmentation client, - Prédiction efficacité énergétique de batiment, - Déploiement d’infrastructure Big Data dans le Cloud, - Gestion de projet IA --> Python, ML, Deep Learning, NLP, Scikit-Learn, Tensorflow, AWS, Streamlit, FastAPI
- Data ScientistOpenclassrooms-CentraleSupélec2023- Sept projets appliqués sur des cas métier (banque, retail, énergie, santé) validés en soutenance - ML & DL en Python , Mise en production/ MLOps : API, dashboards, AWS, PySpark --> Python, Deep Learning, NLP, CNN, scikit-learn, TensorFlow, AWS, Streamlit, Flask
Certifications
- Data Scientist - Expert in Data ScienceOpenClassrooms2023