Remote AI/ML Infrastructure Lead — Scale & Secure AI Platform

Placements24; Queenstown; Remote; NZD 180,000 - 250,000; Full time

Benefits offered by this job

Home office allowance

Generous PTO

Career progression paths

Professional development

Training and certifications

Conference attendance

Job summary

WhatJobs Direct seeks a Remote AI/ML Infrastructure Lead to architect and scale our AI platforms. You will lead a distributed team, design cloud-based infrastructure for data science, model training, deployment and monitoring, and drive security and reliability across environments.

The ideal candidate has 8+ years in infrastructure, DevOps or cloud architecture with a strong focus on AI/ML, plus hands-on experience with AWS/Azure/GCP, Docker, Kubernetes and MLOps tools.

Qualifications

• Bachelor's or Master's degree in CS, Engineering, or related field.
• 8+ years of infrastructure, DevOps, or cloud architecture with AI/ML focus.
• Proven experience leading infra teams on complex projects.
• Expertise in AWS, Azure, or GCP and ML services.

Responsibilities

• Design and implement scalable AI/ML infra on cloud.
• Enforce MLOps practices including CI/CD, model versioning, deployment.
• Manage cloud resources for cost and performance.
• Oversee data pipelines and storage for ML workloads.
• Mentor infrastructure engineers and DevOps staff.
• Ensure reliability, security, and availability of platform.
• Guide integration of new technologies and maintain docs.
• Lead incident response for infra issues.

Skills

Python

Go

Bash

Leadership

Remote collaboration

Problem-solving

Strategic thinking

Education

Bachelor's or Master's degree in Computer Science, Engineering, or related field

Tools

Docker

Kubernetes

Terraform

CloudFormation

MLflow

Kubeflow

Airflow

Job description

WhatJobs Direct seeks a Remote AI/ML Infrastructure Lead to architect and scale our AI platforms. You will lead a distributed team, design cloud-based infrastructure for data science, model training, deployment and monitoring, and drive security and reliability across environments.

The ideal candidate has 8+ years in infrastructure, DevOps or cloud architecture with a strong focus on AI/ML, plus hands-on experience with AWS/Azure/GCP, Docker, Kubernetes and MLOps tools.