[CDI] Senior Generative AI Data Scientist

CDI
Paris
Salaire : Non spécifié
Télétravail non autorisé
Expérience : > 5 ans
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Publicis France
Publicis France

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Descriptif du poste

We are seeking a highly skilled Senior Generative AI Data Scientist to join our team. The ideal candidate will have a strong background in NLP, large models fine tuning, open source community, machine learning and deep learning techniques, as well as experience in generative modeling. The candidate will be responsible for designing, implementing, and optimizing generative models for a variety of applications, including natural language processing, computer vision, and audio processing. The candidate will also be responsible for integrating, deploying and monitoring AI models on the Cloud using services like GIT, Terraform, Jenkins or Kubernetes.

Key Responsibilities:

  • Design, implement, and optimize generative models using machine learning and deep learning techniques.
  • Apply generative models to a variety of applications, including natural language processing, computer vision, and audio processing.
  • Integrate, Deploy and Maintain AI models throughout their lifecycle.
  • Communicate findings to technical and non-technical stakeholders.
  • Collaborate with cross-functional teams to identify new opportunities for generative modeling.

Profil recherché

  • Master's or PhD in Computer Science, Mathematics, Statistics, or related field.
  • 3+ years of data science experience.
  • Active in the open source community, such as HuggingFace, StableDiffusion, etc.
  • Large models fine-tuning experience, familiar with distributed training- Experience with LangChain, Foundation model tuning, Data Augmentation, and Performance Evaluation frameworks.
  • Experience researching and applying large language and generative AI models.
  • Strong background in NLP and/or Computer Vision.
  • Experience with natural language processing, computer vision, or audio processing generative models (including LLM, Diffusion models, GANs, VAEs..).
  • Experience with cloud computing platforms such as AWS or Azure.
  • Experience with using cloud services for deploying and scaling AI models, such as Sagemaker of Azure Machine Learning.
  • Experience in using/implementing/training/fine-tuning/optimizing foundation models or generative models.
  • Proficiency in programming languages such as Python or R.

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