Senior MLOps Engineer — Secure, Scalable ML on Kubernetes

Hustler Marketing LLC; Buenos Aires; Remote; ARS 900,000 - 1,300,000; Full time

Benefits offered by this job

Competitive compensation

Comprehensive benefits

Flexible work environment

Global collaboration

Job summary

Proofpoint is seeking a Senior MLOps Engineer in Cordoba, Argentina to build and maintain production-grade ML infrastructure. You will design scalable CI/CD pipelines, manage containerized services, and ensure secure, compliant deployments across AWS and Azure.

You will collaborate with data scientists and ML engineers to accelerate the path from experimentation to production while monitoring performance and cost. This role emphasizes security, reliability, and scalable ML serving.

Qualifications

• 5+ years of ML experience with PyTorch or TensorFlow.
• Strong Python skills and IaC tooling experience (Terraform/Helm).
• Kubernetes in production environments.
• Hands-on CI/CD (Harness/Jenkins/GitHub Actions).
• Container security: image scanning and remediation.

Responsibilities

• Design and maintain ML CI/CD pipelines for training and deployment.
• Manage container images, base-image governance, and vulnerability remediation.
• Deploy ML inference on Kubernetes across AWS/Azure.
• Lead security/compliance efforts (FedRAMP/SOC2).
• Coordinate with data scientists to move experiments to production.

Skills

Python

Kubernetes

CI/CD

Cloud (AWS/Azure)

ML model serving

Security compliance

Infrastructure as code

SQL

Observability tools

FedRAMP/SOC2 knowledge

Education

BS in CS/Engineering

Tools

Terraform

Helm

Snyk

Docker

GitHub Actions

TorchServe/Triton

Job description

Proofpoint is seeking a Senior MLOps Engineer in Cordoba, Argentina to build and maintain production-grade ML infrastructure. You will design scalable CI/CD pipelines, manage containerized services, and ensure secure, compliant deployments across AWS and Azure.

You will collaborate with data scientists and ML engineers to accelerate the path from experimentation to production while monitoring performance and cost. This role emphasizes security, reliability, and scalable ML serving.