Senior ML Ops Engineer: Scalable ML Infra & Compliance

Fullstack; Buenos Aires; Vor Ort; ARS 1.800.000 - 3.000.000; Vollzeit

Zusammenfassung

Proofpoint is seeking a Senior MLOps Engineer to join the Machine Learning and Data Science Team. You will build and maintain the infrastructure that brings ML models from development to production, ensuring fast, secure shipping of models to production and protecting organizations from security risks.

You will design and operate CI/CD pipelines, manage container images, and deploy scalable inference services across AWS and Azure.

Qualifikationen

• 5+ years of machine learning experience with frameworks like PyTorch or TensorFlow.
• Strong Python programming skills and IaC familiarity (Terraform/Helm).
• Hands-on Kubernetes production experience.
• Experience with CI/CD tools (Harness, Jenkins, GitHub Actions).
• Knowledge of cloud services: AWS (S3, SageMaker, EKS, ECR, IAM/IRSA) and Azure (AKS, Azure ML).
• Understanding security frameworks (FedRAMP/SOC2).
• Experience with ML model serving frameworks (TorchServe, Triton).
• Strong SQL for operational/telemetry data.
• Familiarity with observability tools (Prometheus, Grafana, Datadog).

Aufgaben

• Design, build, and maintain CI/CD pipelines for ML model training and deployment.
• Manage container images, image governance, and vulnerability remediation for ML services.
• Deploy and operate ML inference endpoints on Kubernetes across AWS/Azure.
• Lead FedRAMP compliance efforts for ML infrastructure.
• Manage cloud resources for scalable model serving.
• Collaborate with data scientists to streamline from experiment to production.
• Monitor infrastructure health, model serving performance, and cost efficiency.
• Maintain deployment and security documentation; stay current with MLOps tooling.

Kenntnisse

ML experience

Python programming

SQL skills

Tools

Terraform

Helm

Kubernetes

Harness

GitHub Actions

Jenkins

SageMaker

EKS

ECR

IRSA

Azure ML

Jobbeschreibung

Proofpoint is seeking a Senior MLOps Engineer to join the Machine Learning and Data Science Team. You will build and maintain the infrastructure that brings ML models from development to production, ensuring fast, secure shipping of models to production and protecting organizations from security risks.

You will design and operate CI/CD pipelines, manage container images, and deploy scalable inference services across AWS and Azure.