Senior MLOps Engineer LatAm, Secure ML Infra

Homeward; Buenos Aires; Remote; ARS 185.448.000 - 278.173.000; Vollzeit

Benefits dieser Stelle

Competitive compensation

Comprehensive benefits

Flexible work environment

Wellness and community outreach days

Recognition for contributions

Zusammenfassung

Proofpoint in Córdoba, Argentina seeks a Senior MLOps Engineer to design and operate scalable ML infrastructure from development to production. You will own CI/CD pipelines, container governance, and secure deployment across cloud environments.

You will collaborate with data scientists to streamline the path from experiment to production, monitor performance and costs, and uphold security standards including FedRAMP compliance. This role emphasizes cloud-native, secure ML serving at scale.

Qualifikationen

• 5+ years in ML
• Strong Python
• Production ML experience
• Kubernetes in production
• CI/CD experience with modern tools
• Experience with AWS and Azure
• Knowledge of security frameworks (FedRAMP, SOC2)
• Experience with model serving frameworks

Aufgaben

• Design, build, and maintain CI/CD pipelines for ML 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 to support model serving at scale.
• Collaborate with data scientists to move experiments to production.
• Monitor infrastructure health, performance, and costs.
• Maintain deployment and security architecture documentation.
• Stay current with MLOps tooling and security best practices.

Kenntnisse

Machine Learning

Python

Kubernetes

CI/CD

Cloud (AWS/Azure)

PyTorch

TensorFlow

Security & Compliance

Model Serving

SQL

Tools

Harness

GitHub Actions

Snyk

CIS Benchmarks

Docker

Terraform

Helm

Kubernetes

SageMaker / AKS / EKS

Jobbeschreibung

Proofpoint in Córdoba, Argentina seeks a Senior MLOps Engineer to design and operate scalable ML infrastructure from development to production. You will own CI/CD pipelines, container governance, and secure deployment across cloud environments.

You will collaborate with data scientists to streamline the path from experiment to production, monitor performance and costs, and uphold security standards including FedRAMP compliance. This role emphasizes cloud-native, secure ML serving at scale.