Mid-Level MLOps Engineer

SHOP APOTHEKE EUROPE

MLOps Engineer building and operating secure, reliable ML/AI production services for Redcare Pharmacy, Europe’s leading e-pharmacy. Improving Python systems, Kubernetes infrastructure, CI/CD, and model lifecycle practices.

Posted 9/9/2026full-timeRemote • 🇳🇱 NetherlandsMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and operating containerized ML/AI services, with strong proficiency in Python software engineering, CI/CD pipeline development, and secure software practices. Familiarity with MLOps and DevOps methodologies is essential for optimizing the ML lifecycle and ensuring reliable production deployments.

Highest-signal resume keywords

MLOps ExperiencePython Software EngineeringKubernetes ProficiencyCI/CD Pipeline DevelopmentSecure Software Development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonMLOpsDevOpsContainerizationAutomated TestingVersion ControlModel ValidationModel DeploymentMonitoringSoftware Architecture

Soft Skills

TroubleshootingCollaborationCode Review

Tools & Technologies

KubernetesDockerGitHub ActionsJenkinsMLflowKubeflow

Industry Keywords

ML LifecycleProduction ServicesCost-EfficiencyReliabilityPerformance

Tech Stack

Tools & technologies

DockerJenkinsKubernetesPython

About the role

Key responsibilities & impact

Build and operate containerized ML/AI services using orchestration platforms such as Kubernetes
Troubleshoot production issues and improve reliability, performance, and cost-efficiency of ML/AI services
Develop maintainable, well-tested Python code for production services, automation, and internal tooling
Build and improve CI/CD pipelines for testing, deployment, and model iteration
Implement data and model versioning, validation, and observability across the ML lifecycle
Contribute to technical designs and architecture decisions
Participate in code reviews
Integrate automated security checks into delivery pipelines
Follow secure software development and operations practices

Requirements

What you’ll need

Practical experience in MLOps, DevOps, platform engineering, or software engineering, including deploying and operating ML/AI solutions in production
Solid Python software engineering skills, including automated testing, version control, and code review
Hands-on experience with Docker and container orchestration platforms such as Kubernetes
Experience with CI/CD tools such as GitHub Actions or Jenkins
Familiarity with ML lifecycle practices including model packaging, versioning, validation, deployment, and monitoring
Familiarity with tools such as MLflow or Kubeflow welcome
Solid understanding of software architecture and secure software development and delivery practices

Benefits

Comp & perks

Flexible work location when the job does not require office presence, including up to 20 days per year from anywhere within the EU
Creative team events and regular success celebrations
Professional psychological support via nilo, anonymously and free of charge
Internal and external training opportunities and professional development support
Fully funded Deutschlandticket
Urban Sports Club M membership
Various health and sports benefits