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:

Data Scientist

Job Description