Machine Learning Engineer

AXA IT Solutions is launching an MLOps initiative to modernize actuarial pricing model development by integrating best practices in machine learning operations. The company is developing an AI-powered platform leveraging Generative AI to extract, analyze, and categorize information from large volumes of documents, aiming to streamline document processing workflows and enhance data retrieval.

• Bachelor's or Master's degree in Mathematics, Computer Science, Machine Learning, or a 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 (e.g., AWS, Azure, GCP) and containerization (Docker, Kubernetes).
• Extremely high attention to detail and rigor.

• Create continuous integration templates for model development, ensuring version control, testing, and reproducibility.
• Collaborate with ML Engineering team and actuaries to audit and optimize the reliability and scalability of model training pipelines.
• Develop monitoring strategies for tracking system performance, reliability, and efficiency.
• Manage end-to-end operation of the AI platform to ensure high availability, responsive performance, and secure data handling.
• Oversee integration and management of cloud resources to optimize cost, performance, and compliance with security standards.

The data processing is conducted under the EU General Data Protection Regulation (GDPR) and Polish labor code regulations, with explicit details on personal data handling, rights to object or withdraw consent, and data protection contact information provided. Data will not be used beyond the recruitment process unless consented to. Data is not transferred internationally and is not used for automated profiling.