ML Platform & DevOps Engineer: Cloud Pipelines for AI

present of AI; Australia; Remote; AUD 120,000 - 180,000; Full time

Job summary

Metacognition AI seeks a platform-focused engineer to build and run cloud infrastructure that lets researchers and engineers try ideas and ship software safely. The role emphasizes hands-on DevOps, ML platform work, and secure, self-service tooling.

You’ll work with GitHub Actions pipelines, Terraform or Pulumi, containers, Kubernetes, and cloud providers (AWS or GCP) to scale compute and data, while maintaining guardrails and access controls.

Qualifications

• Hands-on DevOps and ML platform experience.
• Experience with GitHub Actions pipelines, Terraform or Pulumi, containers, Kubernetes, and AWS or GCP.
• Strong grasp of access controls and security, and the ability to build reusable self-service tooling.

Responsibilities

• Build and run the cloud setup that enables researchers and engineers to try ideas and ship software safely.
• Maintain scalable pipelines and platform tooling with guardrails.
• Collaborate with researchers to gate access and ensure secure, reproducible deployments.
• Advise on architecture and best practices for secure, scalable AI workloads.

Skills

GitHub Actions

Terraform

Pulumi

Kubernetes

Containers

AWS

GCP

DevOps

ML platform

Access controls

Tools

GitHub Actions pipelines

Terraform

Pulumi

Kubernetes

Docker

Job description

Metacognition AI seeks a platform-focused engineer to build and run cloud infrastructure that lets researchers and engineers try ideas and ship software safely. The role emphasizes hands-on DevOps, ML platform work, and secure, self-service tooling.

You’ll work with GitHub Actions pipelines, Terraform or Pulumi, containers, Kubernetes, and cloud providers (AWS or GCP) to scale compute and data, while maintaining guardrails and access controls.