Machine Learning Engineer
Offer summary

(Summary generated by AI based on the full job description)

The project focuses on MLOps and an AI-powered platform for automating actuarial model workflows and document processing using GenAI. Required skills include Python, MLOps frameworks like MLFlow, Kedro, Data Science tools (pandas, pyspark, sklearn) and building GenAI agentic workflows (Langchain). Responsibilities cover creating CI for models, collaborating with ML Engineering, monitoring system performance, managing the AI platform, and optimizing cloud resources (AWS, Azure, GCP) with Docker, Kubernetes.

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Machine Learning Engineer

Company: AXA Avanssur SA Oddział II w Polsce

from: 15 June 2026
to: 15 July 2026
170 - 215net (+ VAT)/ hr.B2B contract (full-time)
Offer parameters
level:senior • expert
working mode:remote • hybrid
Warszawa, Wola
Warszawa, WolaChłodna 51View on map

Requirements

Expected technologies

Azure
Docker
Kubernetes
MLFlow
Pandas
PowerBI
Langchain
CI/CD
FastAPI
Python

Operating system

Windows

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

We are launching an MLOps initiative to modernize the development of our actuarial pricing models by integrating best practices in machine learning operations. This project will involve automating model training, deployment, and monitoring processes, ensuring that our actuaries can operate with increased efficiency, reproducibility, and scalability in a production environment.
We are developing an AI-powered platform that leverages GenAI to accurately extract, analyze, and categorize information from large volumes of documents. This platform aims to streamline document processing workflows and enhance the speed and precision of data retrieval across various internal use cases.

This is how we organize our work

This is how we work

in houseyou have influence on the technological solutions appliedyou develop the code "from scratch"you focus on product developmentagilescrum

Team members

3 people:product ownerproject managerIT administrator

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
Company

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

We are an internal software house operating within the international insurance group AXA. We provide IT solutions for the needs of AXA companies in Europe. We work in English on a daily basis, in close-knit teams, carrying out international development projects.
Machine Learning Engineer
170–215 zł / hr. (B2B)
I apply to:
AXA Avanssur SA Oddział II w Polsce
Warszawa, Wola
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