Cloud Infrastructure & DevOps Engineering
Designed and deployed cloud infrastructure for
early-stage startups — from bare VPS to containerized
production environments.
Delivered across 2 client engagements:
— GCP infrastructure setup and configuration
— Docker containerization and orchestration
with Kubernetes
— Linux server hardening and production deployment
— CI/CD pipeline implementation
— Monitoring and incident response setup
Each engagement ran 2–4 weeks, fully remote,
delivered autonomously from architecture to
production handoff.
Stack: GCP · Docker · Kubernetes · Linux · VPS
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2 Peer-Reviewed Publications — ML for Biomedical Classification
Co-authored two peer-reviewed papers on applied
machine learning and deep learning in clinical and biological contexts,
working with CNRS, CEA, and Université Côte d'Azur.
Paper 1 — Bioinformatics:
Introduced PD-CR, a novel primal-dual classification
method outperforming SVM, Random Forests, and PLS-DA
on cancer metabolomics datasets (lung & brain tumors).
Real clinical data from university hospitals of Nice
and Montpellier.
Paper 2 — IEEE/ACM Transactions on Computational Biology and Bioinformatics:
Non-invasive live cell cycle monitoring using a
supervised autoencoder on Quantitative Phase Imaging
data. Achieved 98.6% classification accuracy on
80,000+ cells.
Both projects used real clinical datasets.
No simulations.
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MIND — AI Medical Billing Assistant
MIND automates medical billing coding for French
physicians. The system reads clinical notes and
suggests the correct CCAM codes in real time —
eliminating manual lookup and reducing billing errors.
Built solo from scratch:
— NLP pipeline for clinical note analysis
— Secure architecture for sensitive medical data
— Go-to-market strategy targeting independent
practitioners
Stack: Python, NLP, cloud-native, HIPAA & GDPR-compliant
data architecture.
Role: Sole founder — product, engineering,
and distribution.
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MailSwap — AI Email Classifier for Shopify
MailSwap automatically classifies incoming merchant
emails — refunds, support, billing, shipping — and
routes them to the right team without human triage.
Built end-to-end:
— Custom ML classifier trained on e-commerce
email data
— Shopify App integration
— Production deployment with confidence scoring
Achieved 94%+ classification accuracy in production.
Role: Sole founder — model training, backend engineering, Shopify App Store launch.