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

Datumo; Polska; Hybrid; PLN 223,000 - 335,000; Full time

Benefits offered by this job

100% remote work

Training budget

Cloud certifications support

Private medical care

Sports package

English lessons

Team integrations

Job summary

Datumo, a leading Data & AI company, is hiring for an MLOps/ML Engineering role with deep cloud experience. You will productionize model experiments, automate deployments, and implement observability for scalable model-serving environments across Kubernetes in cloud settings.

You will work with a team of experts on enterprise-grade data platforms, contribute to governance and security, and benefit from a remote-friendly setup and strong training support.

Qualifications

• 3+ years of commercial experience in MLOps, ML Engineering, DevOps, Data Engineering, cloud or backend engineering.
• Experience with Azure or Google Cloud.
• Strong Python skills, including testing, packaging and dependency management.
• Hands-on experience with Docker and Kubernetes.
• 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

• Turning model experiments into production-ready services.
• Building deployment and automation processes.
• Setting up monitoring and observability for model-serving environments.
• Improving reliability, scalability and maintainability of MLOps platforms.
• Working with Kubernetes in cloud environments.
• Supporting governance and security requirements.

Skills

MLOps experience

Python

CI/CD

Git workflows

Deployment automation

English (B2+)

Polish language

Azure/Google Cloud

Tools

Docker

Kubernetes

Terraform

Azure

Google Cloud

Job description

Datumo, a leading Data & AI company, is hiring for an MLOps/ML Engineering role with deep cloud experience. You will productionize model experiments, automate deployments, and implement observability for scalable model-serving environments across Kubernetes in cloud settings.

You will work with a team of experts on enterprise-grade data platforms, contribute to governance and security, and benefit from a remote-friendly setup and strong training support.