onsite
Senior MLOps Engineer - IMPACT GmbH - IMPACT Experts
MLOps Engineer
Lead the design and standardization of scalable ML deployment pipelines using Python, Kubeflow, KServe, and Orbital Pipelines, while defining best practices for model serving, monitoring, and health checks.
About the role
Key Responsibilities
- Develop and standardize deployment solutions for machine‑learning models across the organization.
- Build and maintain scalable deployment pipelines with Kubeflow, KServe, and Orbital Pipelines.
- Create wrappers, SDK extensions, and configuration templates for various ML frameworks.
- Define and enforce best practices for model serving, monitoring, and health checks.
- Produce comprehensive technical documentation and conduct knowledge‑transfer sessions.
Requirements
- Extensive experience with Python and containerized ML deployments.
- Hands‑on expertise in Kubeflow, KServe, and Orbital Pipelines.
- Strong understanding of model serving, monitoring, and health‑check strategies.
- Excellent communication skills for documentation and training.
- Proven ability to design scalable, maintainable ML infrastructure.