Senior ML Ops Engineer - AI Deployment & Governance

Engg; Dublin; On-site; EUR 120,000 - 150,000; Full time

Job summary

Mastercard in Dublin seeks a Senior Machine Learning Ops Engineer to design and operate the pipelines, deployment workflows and production-readiness practices turning models into governed services.

You will own experiment tracking with MLflow or equivalent, manage model registries, implement drift monitoring, and orchestrate training and inference on Databricks, while embedding security and observability across real-time and batch workloads.

Qualifications

• Experience with MLOps tooling and practices: experiment tracking, model registries, and safe deployment patterns.
• Experience supporting AI/ML workloads: deployment pipelines, batch or streaming inference.
• Hands-on CI/CD experience for production AI/ML environments.
• Monitoring, observability, logging, metrics, and tracing for AI workloads.
• Security best practices in cloud and CI/CD: secrets, IAM, least-privilege access.

Responsibilities

• Design and operate ML pipelines for training, evaluation and deployment.
• Implement canary/shadow deployment and model-version gating to prevent breaking changes.
• Orchestrate training/inference on Databricks and maintain job workflows.
• Embed security and governance across pipelines and provide observability.
• Collaborate with engineering, data science, and security teams to improve reliability.

Job description

Mastercard in Dublin seeks a Senior Machine Learning Ops Engineer to design and operate the pipelines, deployment workflows and production-readiness practices turning models into governed services.

You will own experiment tracking with MLflow or equivalent, manage model registries, implement drift monitoring, and orchestrate training and inference on Databricks, while embedding security and observability across real-time and batch workloads.