Senior MLOps Engineer — Kubernetes, FedRAMP & Cloud

Maxit Consulting - Max Corporate Group; Buenos Aires; Remote; ARS 139,086,000 - 200,903,000; Full time

Benefits offered by this job

Competitive compensation

Comprehensive benefits

Flexible work environment

Wellness and community outreach days

Job summary

Proofpoint is seeking a Senior MLOps Engineer for its Machine Learning and Data Science Team. This remote-first role is based in Argentina and focuses on building scalable ML infrastructure from development to production.

You’ll contribute to secure, reliable model serving across multi-cloud environments and collaborate across time zones with global teams. You will design CI/CD pipelines, manage container security, and lead FedRAMP and SOC2 compliance efforts while scaling GPU-backed resources

Qualifications

• 5+ years of machine learning experience with frameworks like PyTorch, TensorFlow
• Strong Python programming and infrastructure-as-code experience
• Hands-on Kubernetes in production environments
• Experience with CI/CD platforms (Harness, Jenkins, GitHub Actions)
• Knowledge of security compliance frameworks (FedRAMP, SOC2)

Responsibilities

• Design, build, and maintain CI/CD pipelines for ML model training and deployment
• Manage container images and vulnerability remediation for ML inference services
• Deploy and operate ML inference endpoints on Kubernetes across AWS/Azure
• Lead FedRAMP compliance efforts for ML infra and security reviews
• Manage GPU nodes and compute clusters to support model serving
• Collaborate with data scientists to streamline from experiment to production
• Monitor infrastructure health, performance, and costs
• Maintain deployment and security documentation

Skills

Strong communication

Tools

Python

Terraform

Helm

Kubernetes

Harness

Jenkins

GitHub Actions

TorchServe

Triton

Job description

Proofpoint is seeking a Senior MLOps Engineer for its Machine Learning and Data Science Team. This remote-first role is based in Argentina and focuses on building scalable ML infrastructure from development to production.

You’ll contribute to secure, reliable model serving across multi-cloud environments and collaborate across time zones with global teams. You will design CI/CD pipelines, manage container security, and lead FedRAMP and SOC2 compliance efforts while scaling GPU-backed resources