Freelancer profile translated to English.
Back to original languageAbout Yakini
Doctoral engineer (Bac+8) specializing in generative AI, I have solid experience in artificial intelligence and natural language processing (NLP / LLM), acquired in research, industrial, and consulting contexts.
How I can help you
I work on technical projects where scalability and business impact are determining factors:
- Python development (scripts, services)
- AI & NLP Solutions (LLM, RAG, semantic search, classification, summarization, document generation)
- Backend / API architecture design
- AI POCs → production deployment
My added value
- PhD Expertise: deep understanding of models and algorithmic challenges
- Industrial Vision: maintainable, testable, and deployable solutions
- Pragmatic Approach: focus on real impact, not unnecessary complexity
- Clear Communication: ability to explain complex topics to non-technical teams
Project Types & Deliverables
- Documented and tested NLP / AI pipelines
- RAG architectures and semantic search engines
- Functional POCs + production deployment/industrialization recommendations
- Production-ready Python backend APIs
- Technical audits and architecture notes
French
Native or bilingual
English
Fluent
Can work on-site
Toulouse (up to 50km)
Experience
- AIRBUS via Expleo GroupGenerative AI EngineerTECHOctober 2025 - Today (8 months)Toulouse, France
- Assessed feasibility and experimented with LLM use cases (Google Gemini) in a highly regulated industrial environment.
- Designed and implemented POC demonstrators to automate documentation analysis and internal workflows.
- Performed prompt engineering, performance evaluation, and technical scoping.
- Expleo GroupPh.D Engineer & Data ScientistTECHJanuary 2024 - Today (2 years and 5 months)Toulouse, France
- Led the end-to-end design and architecture of a Retrieval-Augmented Generation system for domain-specific technical answers.
- Built vector databases, ingestion pipelines, retrieval strategies, and evaluation frameworks.
- Developed and optimized the full POC: retrieval, generation orchestration, and user interaction.
- HNFCPh.D Research | Data ScientistMEDICALDecember 2020 - July 2023 (2 years and 7 months)Besançon, France
- Designed a complete machine learning pipeline for large-scale classification of medical textual data.
- Conducted preprocessing, anonymization, and vectorization and trained ML/transformer-based models.
- Collaborated with clinical teams to refine requirements and validate results.
- Performed this work in the context of PhD research, combining state-of-the-art methods with rigorous experimentation and evaluation.
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Education
- Ph.D in Computer ScienceUniversité Marie Louis et Pasteur2023Ph.D in Computer Science
- Master in Computer ScienceUniversité de Technologie de Belfort-Montbéliard2020Master in Computer Science
Certifications
- LangChain for LLM App DevelopmentSimpliLearn2025
- Machine Learning using PythonSimpliLearn2025