MLOps Engineer at Global Payments

This information is not specified in the job description.

This information is not specified in the job description.

Must-have skills include 4+ years of DevOps, MLOps, or infrastructure engineering experience (preferably 2+ years in AI/ML), hands-on experience with cloud-native services like AWS Bedrock/SageMaker or GCP Vertex AI and GPU infrastructure, strong CI/CD skills with tools like GitHub Actions or ArgoCD, proficiency in Python or Bash, experience with monitoring systems, and deep Kubernetes knowledge.

The company features a dynamic team driven by passion for success, focused on delivering best-in-class payment technology, and emphasizes collaboration with data scientists, AI/ML engineers, and the platform team.

Strong candidates have 4+ years of DevOps/MLOps experience with AI/ML focus, hands-on cloud and Kubernetes expertise, and abilities like high initiative, accuracy, prioritization, and meeting deadlines; bonus for MLOps tooling like MLflow or Kubeflow.