Dev- ML-Ops- / Cloud- Engineer (m/w/d)

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We accompany you from the first conversation, through preparation for your interview with our customer, as well as salary negotiation and acceptance of your employment contract.

Aufgaben

• You design active digital solutions for Cloud-, KI- and ERP-systems with and drive their efficient use and operation forward.
• You modernize and optimize cloud infrastructure continuously, focusing on scalability, stability, and cost efficiency.
• You implement Infrastructure as Code using Docker, Kubernetes, GitLab CI/CD, as well as Argo CD / Argo Workflows, and thus provide fast, reproducible, and scalable infrastructures (including GPU- and LLM-stacks) ready.
• You act cross-functionally as a competent supporter and solution partner for departments.
• You actively share your knowledge in the team, promote the exchange of best practices, and support the establishment of a strong DevOps-/MLOps-culture.

Qualifikation

• Fundamental experience with Kubernetes (cluster management, deployment strategies, resource optimization).
• Practical knowledge in Argo CD / Argo Workflows for CI/CD pipelines and GitOps.
• Safe handling of Git repos (branching strategies, code review processes, integration into CI/CD).
• Experience with GPU drivers and building a scalable LLM-stack (e.g. NVIDIA-stack, CUDA, containerization of models).
• Infrastructure as Code (Terraform, Ansible, etc.) for automated and reproducible deployment.
• Scripting competence with Argo CI/CD for automated, scalable infrastructure processes.
• Knowledge on scalable LLM-infrastructure (resource management, auto-scaling, cost optimization).

Benefits

• Hybrid or remote work as well as flexible working hours.
• Work- and design-space like it belongs to development.
• Participation in company/project success.
• Modern workplace with many possibilities for shaping and further development.

If you bring 1–2 years of operation and maintenance of LLM-infrastructure (production, monitoring, scaling) is it a great advantage!

At least 3 years of DevOps + MLOps or alternatively at least 5 years of pure DevOps knowledge with the desire to dive deeper into MLOps and LLM.

Strong focus on fast and scalable deployment of infrastructure (not