I am a Scientific Research Engineer specializing in Natural Language Processing (NLP), with a focus on model efficiency and multilingual systems. My profile is interdisciplinary, combining research (published work on NMT compression) with full-stack development and systems/infrastructure management, allowing me to own the full path from research to production, not just hand off a model and walk away.

Professional Profile

My research centers on efficient neural machine translation and computational morphology, validated on Arabic, a morphologically rich, low-resource-tooling language that stress-tests methods most work only validates on English or French. The techniques generalize by design. I’ve also built and deployed local LLM infrastructure (Ollama-based) with retrieval-augmented generation pipelines in production, and I’m hands-on with the underlying systems: administering Linux servers and GPU workstations, containerizing services with Docker, and managing deployment end-to-end, from model to served application.

Research & Publications

Selected work on efficient multilingual NMT and computational morphology.

  • A General Framework for Efficient Multilingual Neural Machine Translation: a pruning-based framework for reducing multilingual NMT model size and inference cost while preserving translation quality (validated on English-Arabic).
  • Transformer + VQ-based Arabic Root Extraction (in progress)

View all publications

Research & Interests

My work is driven by a commitment to staying at the forefront of AI research, not chasing hype:

  • Scientific Monitoring: Constant follow-up on advancements in efficient training, NLP, and LLMs.
  • Scientific Reading: Regular reviewer of publications from ArXiv, ACL, and EMNLP.

Expertise

  • NLP & ML: Neural Machine Translation (OpenNMT, Fairseq), model pruning/compression, Transformer architectures, computational morphology, sentiment analysis (BERT, AraBERT), textual similarity (FAISS).
  • LLM Systems: Local/on-prem LLM deployment (Ollama), retrieval-augmented generation (RAG), vector search.
  • Engineering: PyTorch, REST API development (FastAPI, Django), Frontend (React, TypeScript).
  • Systems & Infrastructure: Linux server and GPU workstation administration, Docker containerization and app deployment, CI/CD-style deployment workflows, Database management (PostgreSQL, MongoDB).

Languages

  • French: Native/Fluent
  • English: Professional
  • Arabic: Native/Fluent

“I bridge the gap between efficient NLP research and scalable production systems.”