ML / LLM Ops Engineer (m/f/d)

MeJuvante; Gau-Algesheim; Vor Ort; EUR 90.000 - 130.000; Vollzeit

Zusammenfassung

MeJuvante GmbH in Germany seeks a senior ML Ops engineer to design and run ML and LLM systems in production, focusing on reliability and governance.

You will build MLOps and LLMOps architectures with CI/CD and model management, design cloud infra with Terraform/Ansible, and embed information security, drift detection, and cost monitoring into operations.

Qualifikationen

• Operate and architect ML and LLM solutions in production.
• Build MLOps / LLMOps architectures including CI/CD and model management.
• Design cloud architectures (AWS / Azure / GCP) with containerisation and IaC (Terraform, Ansible).
• Embed information security into the AI context.
• Own governance and quality management for ML and LLM models.
• Automate and monitor production ML/LLM systems, including drift and cost.

Aufgaben

• Operate and architect ML and LLM solutions in production.
• Build MLOps / LLMOps architectures including CI/CD and model management.
• Design cloud architectures (AWS / Azure / GCP) with containerisation and IaC (Terraform, Ansible).
• Embed information security into the AI context.
• Own governance and quality management for ML and LLM models.
• Automate and monitor production ML/LLM systems, including drift and cost.

Kenntnisse

MLOps

LLMOps

CI/CD

Cloud architecture

Terraform

Ansible

Monitoring

Governance

Security

Cost optimization

Tools

Terraform

Ansible

AWS

Azure

GCP

Jobbeschreibung

Permanent role running ML and LLM systems in production: MLOps and LLMOps architecture, model management, monitoring, and the governance evidence that keeps them auditable.

• Operate and architect ML and LLM solutions in production
• Build MLOps / LLMOps architectures including CI/CD and model management
• Design cloud architectures (AWS / Azure / GCP) with containerisation and IaC (Terraform, Ansible)
• Embed information security into the AI context
• Own governance and quality management for ML and LLM models
• Automate and monitor production ML/LLM systems, including drift and cost