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Aymane NouhailAN

Aymane Nouhail

AI Engineer

€550/day
Paris, FR
0-2 years

Average response time: 1 hour

About Aymane

  • French

    Native or bilingual

  • English

    Native or bilingual

Can work on-site
Paris (up to 50km)

Experience

  • Publicis Re:Sources
    GenAI Data Scientist
    October 2024 - Today (1 year and 8 months)
    Paris, France
    Spearheaded the V2 ground-up rewrite of the company's agentic AI platform as technical lead, driving architecture decisions and coordinating development across creative, media, and PR teams.
    • • Architected a production multi-tenant agentic platform serving 4 enterprise clients across real-time collaboration, docu ment editing, and conversational AI, processing 300K+ monthly requests through a shared provider-agnostic LLM layer supporting Claude (Anthropic), Gemini (Google), and GPT (OpenAI).
    • • Designed a modular agent architecture with clear orchestration boundaries between planning, execution, and tool layers, enabling new client workflows to ship without modifying core platform logic.
    • • Built an evaluation and observability stack combining agent testing frameworks with Langfuse tracing, Application Insights, and structured logging to monitor agent behavior, latency, and failure modes in production.
    • • Reduced campaign production time by 30% by co-building a RAG pipeline for Carrefour radio-ad generation (500+ historical campaigns ingested, LLM-drafted scripts with brand-tone consistency).
  • Green Energy Park
    Data Science Intern
    April 2024 - July 2024 (3 months)
    Ben Guerir, Morocco
    Built an end-to-end voice-first agentic assistant on Raspberry Pi, combining wake-word detection, automatic speech recog nition (ASR), and a retrieval-augmented LLM pipeline for hands-free smart-home control and knowledge-base Q&A.
    • • Designed a streaming speech-to-text pipeline with wake-word detection feeding a context-aware LLM inference layer, enabling fully hands-free natural-language control of IoT devices.
    • • Implemented a RAG agent grounded on a structured knowledge base, supporting device automation commands, multi media queries, and open-domain Q&A with low-latency on-device inference.

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Education

  • MSc in Machine Learning for Data Science
    Université Paris Cité
    2026
    MSc in Machine Learning for Data Science
  • BSc in Data Science
    Mohammed VI Polytechnic University
    2024
    BSc in Data Science

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