MLOps Engineer

Job Summary

We are looking for an MLOps Engineer to support actuarial model development and run a high-availability AI platform. The role focuses on building reproducible CI/CD for models, operating model training pipelines, and ensuring secure, scalable document ingestion and processing.

Key Responsibilities

• Create CI templates for model versioning, testing and reproducibility.
• Audit and optimise model training pipelines with ML engineers and actuaries.
• Develop monitoring for performance, reliability and efficiency.
• Manage platform operations to ensure availability, performance and secure data handling.
• Integrate and optimise cloud resources for cost, performance and compliance.

Requirements

• Bachelor's or Master's in Mathematics, CS, ML or related field.
• Proficient with pandas, PySpark, scikit-learn and SHAP.
• Experience with MLOps tools: MLflow, Kedro/Airflow, Hyperopt/Optuna, Great Expectations.
• Familiarity building GenAI agentic workflows (LangChain or smolagents).
• Experience with CI/CD (GitHub Actions or similar) and serving models via Flask/FastAPI.
• Cloud and containerization experience (AWS/Azure/GCP, Docker, Kubernetes).
• High attention to detail and rigor; English at least B2.

Nice to have

• French A2/B1.