Senior MLOps Engineer – Flexible Work Environment

202 Proofpoint Argentina SRL; Córdoba; Vor Ort; ARS 139.086.000 - 200.903.000; Vollzeit

Benefits dieser Stelle

Competitive compensation

Comprehensive benefits

Flexible work environment

Wellness days and outreach

Recognition program

Global collaboration opportunities

Career growth

Zusammenfassung

Proofpoint is seeking a Senior MLOps Engineer to build and maintain the infrastructure that brings ML models from development to production. You will scale inference endpoints and ensure secure, compliant deployments across cloud environments.

You will collaborate with data scientists and ML engineers to streamline the path from experiment to production, monitor performance, and drive cost efficiency in a global, mission-driven team.

Qualifikationen

• 5+ years of machine learning experience with frameworks like PyTorch or TensorFlow.
• Strong Python programming skills.
• Production experience with Kubernetes and CI/CD.
• Experience with AWS and Azure ML services.

Aufgaben

• Design, build, and maintain CI/CD pipelines for ML model training and deployment.
• Manage container images, base image governance, and vulnerability remediation.
• Deploy and operate ML inference endpoints on Kubernetes across AWS and Azure.
• Lead FedRAMP compliance efforts for ML infrastructure.
• Manage cloud resources (GPU nodes, compute clusters, IRSA configurations) for model serving.
• Collaborate with data scientists and ML engineers to move from experiment to production.
• Monitor infrastructure health, model serving performance, cost efficiency.
• Maintain deployment and security documentation.
• Stay current with MLOps tooling and cloud-native security practices.

Kenntnisse

Python

Kubernetes

CI/CD

Terraform

AWS

Azure

SageMaker

GitHub Actions

Jenkins

TorchServe

SQL

Tools

Terraform

Helm

Docker

Harness

Jobbeschreibung

Proofpoint is seeking a Senior MLOps Engineer to build and maintain the infrastructure that brings ML models from development to production. You will scale inference endpoints and ensure secure, compliant deployments across cloud environments.

You will collaborate with data scientists and ML engineers to streamline the path from experiment to production, monitor performance, and drive cost efficiency in a global, mission-driven team.