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David HuangDH

David Huang

Machine learning engineer - AI engineer

€750/day
Paris, FR
3-7 years

Average response time: 12 hours

About David

Ingénieur spécialisé en intelligence artificielle et en traitement automatique du langage, je développe des solutions d’IA générative. Mon expertise couvre la conception de systèmes de NLP industriels, l’optimisation de la recherche d’information et le déploiement d’applications d’IA à grande échelle. Passionné par l’état de l’art en IA, je combine recherche scientifique et mise en production de solutions intelligentes.

Ma démarche repose sur une méthodologie itérative, favorisant le passage rapide du POC à la production en respectant les meilleurs standards de qualité logicielle et d’ingénierie des systèmes d’IA.
  • French

    Native or bilingual

  • English

    Fluent

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

Experience

  • Doctrine
    Machine learning engineer
    January 2022 - February 2026 (4 years and 1 month)
    Paris, France
    - Led the design and deployment of a production-grade legal AI assistant leveraging RAG pipelines and agentic architectures (OpenAI, Gemini, Mistral), improving access to legal information at scale

    - Built multi-stage retrieval systems combining key-word and vector search with Elasticsearch, with re-ranking pipelines to optimize relevance and latency

    - Designed and optimized RAG architectures (chunking strategies, embeddings, retrieval orchestration, source attribution) for high-precision legal use cases

    - Implemented evaluation and benchmarking frameworks for LLM systems (retrieval quality, answer accuracy, latency), driving iterative product improvements

    - Led A/B testing and experimentation on systems relevance

    - Deployed and scaled models in production with robust MLOps pipelines (MLflow, Vertex AI, SageMaker, DVC), ensuring monitoring, reliability and observability

    - Trained and fine-tuned NLP models (BERT, HuggingFace) for legal tasks, including knowledge graph construction and domain adaptation

    - Contributed to technical strategy and AI watch, including LLM optimization techniques (fine-tuning, distillation, RLHF) and emerging frameworks (vLLM, DSPy, langgraph, literalAI)
    Elasticsearch MLOps LLM Agentic AI RAG
  • OCTO TECHNOLOGY
    Data engineer
    September 2020 - December 2021 (1 year and 3 months)
    Paris, France
    Client : Total energy

    Mission : Hydrogen network management webapp
    - Real-time network status monitoring (Flask, Docker, Sendgrid). Network state prediction.
    - Data streaming pipeline (Azure Cloud Event Hub, Spark Databricks). Physical network modeling.

    Mission : Energy consumption prediction for refineries
    - Data ingestion pipeline (PostgreSQL).
    - Backend development
    - Energy consumption prediction, timeseries forecasting (Pandas, Scikit-Learn)
    PostgreSQL Microsoft Azure Python
  • OCTO TECHNOLOGY
    ML engineer
    May 2020 - August 2020 (3 months)
    Paris, France
    Client : Airbus
    Mission : Defect detection on the production line using computer vision
    - Webapp development (Vue.js, MongoDB, Docker, FastAPI).
    - Deep learning model training (Tensorflow, YOLOv3).
    - Deployment on embedded systems (Microsoft IoT edge).
    FastAPI Deep Learning YOLO Docker

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Education

  • Azure DP-100: Designing and implementing a data science solution
    Azure DP-100: Designing and implementing a data science solution
  • Engineering master degree
    IMT Atlantique Nantes
    2019
    Engineering master degree

Skill set

Categories