MLOps Engineer — Enterprise AI Platform (Remote)

Stermedia; Wrocław; Remote; PLN 190,000 - 234,000; Full time

Benefits offered by this job

Flexible hours

Remote work possibility

Self-development budget

Chillout room & events

MultiSport

LuxMed

Job summary

Stermedia is seeking an experienced MLOps Engineer to help build, automate, and scale production-grade AI and ML solutions. You will work at the intersection of ML, cloud engineering, and DevOps to transform models into reliable, scalable services.

Collaborate with data scientists and cloud engineers to deploy, monitor, and maintain ML systems using modern cloud-native tools. The role offers remote work options and a dynamic, tech-forward environment.

Qualifications

• 2+ years in MLOps, DevOps, Cloud Engineering, ML Engineering, or related field.
• Strong Python programming skills (clean, maintainable, testable).
• Docker & Kubernetes: containerization and Kubernetes deployments.
• Cloud Platforms: Azure, AWS, or GCP exposure.
• CI/CD: automated build/test/deploy with GitLab CI or GitHub Actions.
• MLOps Fundamentals: ML workflows, model deployment, experiment tracking.
• Workflow Orchestration: Kubeflow Pipelines, Airflow, or Argo Workflows.
• Infrastructure as Code: Terraform or similar.
• Monitoring: Prometheus, Grafana, or equivalents.
• English: B2+ level for technical discussions and collaboration.

Responsibilities

• Build, automate, and scale production-grade ML solutions.
• Collaborate with Data Scientists, ML Engineers, and Cloud Engineers to deploy and maintain systems.
• Improve model deployment processes and ML infrastructure.
• Monitor, log, and ensure reliability of ML services.

Skills

Python

Docker & Kubernetes

Cloud Platforms

CI/CD pipelines

MLOps Fundamentals

Workflow Orchestration

Infrastructure as Code

Monitoring

English (B2+)

Tools

Kubeflow

Airflow

Argo Workflows

Terraform

Job description

Stermedia is seeking an experienced MLOps Engineer to help build, automate, and scale production-grade AI and ML solutions. You will work at the intersection of ML, cloud engineering, and DevOps to transform models into reliable, scalable services.

Collaborate with data scientists and cloud engineers to deploy, monitor, and maintain ML systems using modern cloud-native tools. The role offers remote work options and a dynamic, tech-forward environment.