Experience — Adil Eddarif

AI engineering roles at the Cheikh Zaïd Foundation, Attijariwafa Bank and Arteka, with measured outcomes: 100% emergency recall, 96.9% X-ray accuracy.

Artificial Intelligence Engineer — Cheikh Zaïd Foundation (May 2026 – Present)

Production medical AI for Cheikh Zaid Hospital: a clinical RAG assistant and a chest X-ray triage pipeline.

Stack: RAG, FAISS, BM25, FastAPI, PyTorch, ResNet50, YOLOv8, pytest.

• Built an end-to-end medical-orientation RAG assistant on a two-stage hybrid retrieval architecture (FAISS + BM25 + cross-encoder reranking), served via FastAPI with rule-based symptom routing and emergency red-flag detection.
• Designed an evaluation framework over a 1,000-question golden dataset with an independent LLM judge scoring faithfulness and hallucination, which surfaced a safety-routing bug and lifted emergency recall from 50% to 100%.
• Hardened the assistant for production: prompt-injection filtering ahead of every LLM call, deduplication, version-safe index rebuilding, and a strict advisory-only workflow that defers to physicians and emergency services, covered by a pytest suite.
• Built a two-stage chest X-ray triage pipeline (ResNet50 classifier + YOLOv8 detector) reaching 96.9% accuracy and 99.7% AUC on a 522-image held-out test set.
• Designed a doctor-in-the-loop clinical workflow that persists physician corrections as structured data for monitoring and retraining.

Data Scientist — Attijariwafa Bank (Feb 2025 – Mar 2026)

Predictive financial models and internal AI tooling.

Stack: Python, Scikit-learn, MLflow, Docker, NLP, Flask.

• Built supervised models estimating annual business targets, replacing heuristic rules (0.90 R²).
• Deployed an MLOps pipeline on MLflow covering tracking, validation (MAE, RMSE) and model versioning.
• Designed an internal RAG chatbot for semantic search across financial documents.

AI & Computer Vision Intern — Arteka (Aug 2024 – Sep 2024)

Computer vision for medical imaging diagnosis.

Stack: OpenCV, PyTorch, GANs, Python.

• Developed image recognition algorithms for medical imaging with OpenCV and GANs.
• Generated synthetic cancer-cell datasets to address data scarcity and improve robustness.
• Contributed to the proof of concept for an AI-assisted diagnostic system.