Remote MLOps Engineer - Cloud (GCP/Azure/Kubernetes)

Datumo

Warszawa

On-site

PLN 223,000 - 335,000

Full time

14 days+

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Benefits offered by this job

Private medical care
Sports package
English lessons
Team integrations
Training budget

Job summary

Datumo is a Big Data & Cloud company focused on data platforms, data engineering, cloud modernization and practical AI solutions. We operate with a Poland-based remote team and work with enterprise-scale data environments.

We are building an end-to-end ML platform and related analytics capabilities using Databricks, Azure ML and Vertex AI to support real-time data-driven decisions across industries.

Qualifications

  • 3+ years of commercial MLOps, ML engineering, or DevOps experience.
  • Experience with Azure or Google Cloud.
  • Strong Python skills, including testing and packaging.
  • Hands-on Docker and Kubernetes experience.
  • Practical knowledge of CI/CD, Git workflows and deployment automation.
  • Understanding of the ML lifecycle: tracking, versioning, deployment, inference, monitoring and rollback.
  • Basic knowledge of ML concepts, including metrics, reproducibility and data or model drift.
  • English at B2+ level and communicative Polish.

Responsibilities

  • Turn model experiments into production-ready services.
  • Build deployment and automation processes.
  • Set up monitoring and observability for model-serving environments.
  • Improve reliability, scalability and maintainability of MLOps platforms.
  • Work with Kubernetes in cloud environments.
  • Support governance and security requirements.

Skills

MLOps
Python
Docker
Kubernetes
CI/CD
Cloud (Azure/Google)
English (B2+)
Polish language

Tools

Databricks
Vertex AI
Azure ML
Prometheus
Grafana

Job description

Datumo is a Big Data & Cloud company focused on data platforms, data engineering, cloud modernization and practical AI solutions. We operate with a Poland-based remote team and work with enterprise-scale data environments.

We are building an end-to-end ML platform and related analytics capabilities using Databricks, Azure ML and Vertex AI to support real-time data-driven decisions across industries.

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