MLOps Engineer

• Bachelor's or Master's degree in Mathematics, Computer Science, Machine Learning, or related field
• Mastery of Data Science frameworks (pandas, pyspark, sklearn, shap) and MLOps frameworks (MLFlow, Kedro/Airflow, Hyperopt/Optuna, Great Expectations) in Python
• Experience 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 serving models with APIs using Flask or FastAPI
• Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes)
• Extremely high attention to detail and rigor
• English language proficiency at least B2 level

Nice to have:

• French language proficiency A2/B1

• Create continuous integration templates tailored for model development ensuring version control, testing, and reproducibility of actuarial pricing models and datasets
• Close work with ML Engineering team and actuaries to audit and optimize reliability and scalability of model training pipelines
• Develop monitoring strategies to track performance, reliability, and efficiency of the system
• Manage end-to-end operation of AI platform to guarantee high availability, responsive performance, and secure data handling during document ingestion and processing
• Oversee integration and management of cloud resources to optimize cost, performance, and compliance with security standards