Senior ML Ops Engineer (m/f/d)
$84,240–$116,640 year
Remote · Köln, North Rhine-Westphalia, Germany
Job Summary
Develop and maintain CI/CD pipelines for deploying ML and LLM models in production; optimize the deployment process for LLMs considering cost, latency, and scalability; automate model retraining and redeployment; manage cloud and on-premise infrastructure on AWS, GCP, or Azure; work with Docker and Kubernetes for scalable, resilient model deployment; implement data versioning and validation; use MLflow for tracking experiments and reproducibility; document MLOps/LLMOps practices and mentor teammates on deployment best practices.
Required Qualifications
- Hands-on experience in MLOps/DevOps or related role
- Experience deploying ML/LLM models
- Proficiency with cloud platforms (AWS, Azure, GCP)
- Containerization (Docker, Kubernetes)
- Experience with CI/CD tools (Github Actions, Jenkins)
- ML workflow tools (MLflow, Kubeflow)
- Scripting in Python/Bash
- Infrastructure-as-code (Terraform)
- Git or version control
- Strong analytical and problem-solving skills
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