MLOps Engineer (m/f/d)
The MLOps Engineer will design, containerize, and maintain machine‑learning services on Kubernetes, ensuring reliable deployment pipelines with tools like GitHub Actions and Jenkins. They will also implement model versioning, validation, and monitoring to keep AI solutions secure and observable in production.
Skills required
About this role
About the Role:
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.
About your tasks:
- Build and operate containerized services using orchestration platforms such as Kubernetes.
- Troubleshoot production issues and improve the reliability, performance, and cost-efficiency of ML/AI services.
- Develop maintainable and well-tested Python code for production services, automation, and internal tooling.
- Build and improve CI/CD pipelines for ML/AI services, enabling reliable testing, deployment, and model iteration.
- Implement data and model versioning, validation, and observability to support integrity and reproducibility throughout the ML lifecycle.
- Contribute to technical designs and architecture decisions, and participate in code reviews.
- Integrate automated security checks into delivery pipelines and follow secure development and operations practices.
Qualifications
About you:
- Practical experience in MLOps, DevOps, platform engineering, or software engineering, including deploying and operating ML/AI solutions in production.
- Solid software engineering skills in Python, 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 such as model packaging, versioning, validation, deployment, and monitoring; experience with tools such as MLflow or Kubeflow is welcome.
- A solid understanding of software architecture and secure software development and delivery practices.
Additional Information
About your Benefits:
In order to provide our employees with the best possible support for their individual needs, we offer a variety of attractive benefits:
Work from Home: If your job doesn't require you to be in the office, you can be flexible about where you work – even up to 20 days a year from anywhere within the EU.
Redcare Events: We promote team cohesion through creative team events and celebrate our joint successes at regular events.
Mental Health: If you feel overwhelmed privately or professionally, you can get professional support from a psychologist quickly and easily via nilo - anonymously and free of charge.
Personal development: We are all constantly learning. That's why we support and promote your professional development through internal and external training opportunities and help you to develop further.
Mobility: Your commute to work is important to us. That's why we provide our employees with a fully funded Deutschlandticket, which you can use at any time.
Sport & Health: Your well-being is our top priority. That's why we offer you various ways to do something for your health. Benefit from an M membership of the Urban Sports Club and take advantage of a wide range of sports to suit your interests.
