Senior ML Ops Engineer: AI Deployment & Observability

Mastercard; Malahide; On-site; EUR 110,000 - 150,000; Full time

Job summary

Mastercard in Ireland is seeking a Senior Machine Learning Ops - AI Engineering to design and operate pipelines, deployment workflows, and production-readiness practices turning trained models into reliable services. You will own experiment tracking with MLflow, implement model monitoring, orchestrate Databricks workloads, and embed security across CI/CD.

This role requires hands-on cloud experience (AWS/Azure/GCP), Databricks, Terraform, Docker, and Kubernetes, plus a collaborative,

Qualifications

• Experience with MLOps tooling: experiment tracking, model registries, and safe deployment/rollout.
• Experience supporting AI/ML workloads: deployment pipelines, batch or streaming inference.
• Hands-on experience building CI/CD pipelines in production environments.
• Familiarity with monitoring and observability practices for AI workloads.
• Security best practices in cloud and CI/CD environments, IAM and least privilege.
• Experience with Databricks or a similar unified data/AI platform.
• Hands-on cloud experience (AWS/Azure/GCP) as a consumer of managed services.
• Infrastructure-as-code tools (Terraform) to provision resources.
• Containerization with Docker; Kubernetes exposure is a plus.
• Software delivery practices: version control, automated testing, release discipline.

Responsibilities

• Own experiment tracking and model registry practices for model versioning and lifecycle.
• Implement drift and model-performance monitoring for AI models.
• Implement safe model release and rollout mechanisms with canary/shadow patterns.
• Orchestrate training and inference workloads on Databricks with workflows.
• Design observability: logging, metrics, tracing for real-time and batch workloads.
• Set up automated evaluation gates for offline metrics and model degradation.
• Design and build CI/CD pipelines for AI/data workloads and security integration.
• Embed security into pipelines: secrets management and least-privilege access.
• Onboard platform services onto central infrastructure and support incident response.

Skills

MLflow

Model deployment

CI/CD pipelines

Databricks

Docker

Kubernetes

AWS

Azure

GCP

Terraform

Tools

Databricks

MLflow

Terraform

Docker

Kubernetes

AWS

Azure

GCP

Job description

Mastercard in Ireland is seeking a Senior Machine Learning Ops - AI Engineering to design and operate pipelines, deployment workflows, and production-readiness practices turning trained models into reliable services. You will own experiment tracking with MLflow, implement model monitoring, orchestrate Databricks workloads, and embed security across CI/CD.

This role requires hands-on cloud experience (AWS/Azure/GCP), Databricks, Terraform, Docker, and Kubernetes, plus a collaborative,