Mid-Level MLOps Engineer (m/f/d) Cologne Posted on 09.09.2026

Redcare Pharmacy

Deutschland

On-site

EUR 90,000 - 130,000

Full time

14 days+

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Job summary

Redcare Pharmacy is hiring an MLOps Engineer (m/f/d) to build, operate, and improve ML/AI solutions in production. You will work at the intersection of data science and software engineering, turning models into secure, maintainable services.

You will collaborate with data scientists and engineers in cross-functional teams and help to advance MLOps practices and our platform across the lifecycle.

Qualifications

  • Experience deploying ML models to production environments.
  • Ability to collaborates with data scientists and software engineers.

Responsibilities

  • Build, operate, and improve ML/AI solutions in production.
  • Collaborate with data scientists and engineers in cross-functional teams.
  • Contribute to continuous improvement of MLOps practices and platform.

Skills

MLOps
CI/CD
DevOps
Model monitoring

Tools

Python
Docker
Kubernetes
GitHub Actions
Jenkins
MLflow
Kubeflow
CI/CD
Git/version control
Automated testing
Model packaging
Model validation
Observability
Secure software development

Job description

About Redcare Pharmacy:

AsEurope’s No.1 e-pharmacyRedcare Pharmacy is powered by passionate teams and cutting-edge innovation. We strive to create a healthy collaborative work environment where every employee feels valued and inspired to contribute to our vision“Until every human has their health”. If you’re seeking a career that offers purpose and aligns with your values join us and start your#Redcareertoday.

About theRole:

We are seeking a MLOps Engineer (m/f/d) to build, operate, and improve ML/AI solutions in production. You will work at the intersection of data science and software engineering, helping to turn models into secure, maintainable, and reliable production services. You’ll collaborate with data scientists and engineers in cross-functional product teams and contribute to the continuous improvement of our MLOps practices and platform.

Tech stack:

Python, Docker, Kubernetes, GitHub Actions, Jenkins, MLflow, Kubeflow, CI/CD, Git/version control, automated testing, model packaging and versioning, model validation and monitoring, observability, and secure software development/DevOps practices.

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