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Data Scientist

Open 51d
  • Design & Deploy: Create machine learning models and tailored AI solutions.
  • Innovate: Fine-tune and extend Large Language Models (LLMs) including open-source and commercial models.
  • Optimize: Implement Retrieval-Augmented Generation (RAG) techniques for enhanced model efficiency.
  • Analyze: Perform exploratory data analysis and feature engineering to unlock better model performance.
  • Build Generative AI: Develop cutting-edge models for content creation, process automation, and innovation.
  • Apply Traditional ML: Utilize decision trees, SVMs, neural networks, and more to solve diverse problems.
  • Collaborate: Work alongside data engineers, product managers, and stakeholders.
  • Quality Assurance: Ensure high-quality AI solutions through rigorous testing and validation.
  • Document & Share: Maintain technical documentation for knowledge sharing and reproducibility.

Your Must-Have Skills:

  • Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field.
  • 3+ years of hands-on experience in machine learning and AI development.
  • Strong expertise in Generative AI (model training, fine-tuning, and deployment).
  • Experience with open-source and commercial LLMs.
  • Proficiency in implementing RAG techniques.
  • Experience with vector databases.
  • Advanced programming skills in Python with frameworks like TensorFlow, PyTorch, and Hugging Face.
  • Deep understanding of NLP techniques and architectures.
  • Practical experience with traditional AI/ML methods such as decision trees, SVMs, and neural networks. Practical experience with traditional AI/ML methods such as decision trees, SVMs, clustering and neural networks.
  • Familiarity with cloud platforms (AWS, GCP, or Azure) for AI/ML deployments.
  • Knowledge of MLOps practices and tools.
  • Strong problem-solving and analytical skills.
  • Effective communication in public and teamwork skills.
  • Fluency in English (C1 level or higher) is mandatory.
  • Willingness to learn French.

Nice-to-Have Skills:

  • Knowledge of reinforcement learning from human feedback (RLHF).
  • Familiarity with prompt engineering.
  • Understanding of ethical AI principles and model interpretability.
  • Fluency in French is a plus.

See also

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