JJobsSonar

MLOps Engineer

DCG · Warsaw, Mazowieckie, Poland

AI/MLRemote

About this role

The MLOps Engineer will be responsible for creating continuous integration templates for model development, ensuring version control, testing, and reproducibility of actuarial pricing models and datasets. They will collaborate closely with the ML Engineering team and actuaries to audit and optimize model training pipelines for reliability and scalability. The role involves developing monitoring strategies to track system performance, reliability, and efficiency, as well as managing the end-to-end operation of the AI platform for high availability, secure data handling, and responsive performance. The candidate will also oversee cloud resource integration and management to optimize cost, performance, and compliance with security standards.

Skills & technologies

Must have

  • Python
  • pandas
  • pyspark
  • sklearn
  • shap
  • MLFlow
  • Kedro
  • Airflow
  • Hyperopt
  • Optuna
  • Great Expectations
  • Langchain
  • smolagents
  • PowerBI
  • Tableau
  • CI/CD
  • Github Actions
  • Flask
  • FastAPI
  • AWS
  • Azure
  • GCP
  • Docker
  • Kubernetes

Nice to have

  • French

Read full description

About the job As a recruitment company, DCG understands that every business is powered by experienced professionals. Our management style and partnership approach enable us to meet your needs and provide continuous support. Due to our ongoing growth and the large number of recruitment projects we undertake for our partners, we are currently looking for: MLOps Engineer 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 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 English - at least B2 level Nice to have: French - A2/B1 Offer: Private medical care Co-financing for the sports card Constant support of dedicated consultant Employee referral program
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