Machine Learning Engineer (F/M)

Our requirements

• 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.

Your 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.

About the project

This is how we organize our work

This is how we work on a project

• Clean Code
• code quality measures
• code review
• design patterns
• static code analysis
• BDD
• pair programming
• TDD
• architect / technical leader support
• Continuous Deployment
• Continuous Integration
• DevOps
• active monitoring
• documentation
• issue tracking tools
• integration tests
• test automation
• testing environments
• unit tests

Development opportunities we offer

• conferences in Poland
• development budget
• industry-specific e-learning platforms
• intracompany training
• soft skills training
• substantive support from technological leaders
• technical knowledge exchange within the company

Benefits

• sharing the costs of sports activities
• private medical care
• sharing the costs of foreign language classes
• sharing the costs of professional training & courses
• remote work opportunities
• flexible working time
• fruits
• integration events
• corporate gym
• corporate sports team
• no dress code
• video games at work
• coffee / tea
• drinks
• parking space for employees
• leisure zone
• sharing the commuting costs
• employee referral program

AXA Avanssur SA Oddział II w Polsce