Responsibilities
- Create continuous integration templates tailored for model development ensuring version control, testing, and reproducibility of our actuarial pricing models and datasets
- Close work with members of the ML Engineering team and actuaries to audit and optimize the reliability and scalability of the actuaries' model training pipelines
- Develop effective monitoring strategies to track the performance, reliability, and efficiency of the system
- Manage the end-to-end operation of the AI platform to guarantee high availability, responsive performance, and secure data handling during document ingestion and processing
- Oversee the integration and management of cloud resources to optimize cost, performance, and compliance with security standards, thereby enabling continuous innovation on the platform
Basic qualifications
- Bachelor's or Master's degree in Mathematics, Computer Science, Machine Learning, or related field
- Mastery over Data Science frameworks (pandas, pyspark, sklearn and shap) and MLOPS frameworks (MLFlow, Kedro/Airflow, Hyperopt/Optuna and Great Expectations) in Python
- Experience with building GenAI agentic workflows using Langchain or smolagents
- Basic familiarity with Dashboarding tools (PowerBI/Tableau)
- Strong understanding of DevOps methodologies (CI/CD) and experience implementing Github Actions (or similar) workflows
- Experience with serving models with APIs using Flask or FastAPI
- Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization (e.g., Docker, Kubernetes)
- Extremely high attention to detail and rigor
- English - at least B2 level
Preferred qualifications
- French - A2/B1
- Private medical care
- Co-financing for the sports card
- Constant support of dedicated consultant
- Employee referral program
Tags & focus areas
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