AI Platform Engineer — Hybrid, Build Scalable ML Pipelines

Placements24; Queenstown; Remote; AUD 97,000 - 145,000; Full time

Benefits offered by this job

Hybrid work model

Competitive salary and incentives

Health, dental, and vision benefits

Professional development opportunities

Job summary

Placements24 client in Queenstown is seeking a skilled AI Platform Engineer to join the team. You will design, build, and maintain scalable AI/ML platforms and infrastructure, and streamline MLOps workflows to support rapid model development and deployment.

You will collaborate with data scientists and ML engineers, implement data management, feature stores and model versioning, and ensure performance, security, and cost efficiency of the platforms.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related technical field.
• 4+ years of software engineering or DevOps experience focusing on AI/ML infrastructure.
• Experience with cloud platforms (AWS, Azure, or GCP) and containerization (Docker, Kubernetes).

Responsibilities

• Design, build, and maintain scalable AI/ML platforms and infrastructure.
• Develop and automate MLOps pipelines for model training, deployment, monitoring, and management.
• Implement data management, feature stores, and model versioning solutions.
• Collaborate with data scientists and ML engineers to understand infrastructure needs and provide support.
• Ensure performance, security, and cost-effectiveness of AI platforms.

Skills

AI/ML infrastructure

CI/CD for ML workflows

Cloud platforms

Docker & Kubernetes

Python scripting

Education

Bachelor's degree in Computer Science or related field

Tools

Terraform

Job description

Placements24 client in Queenstown is seeking a skilled AI Platform Engineer to join the team. You will design, build, and maintain scalable AI/ML platforms and infrastructure, and streamline MLOps workflows to support rapid model development and deployment.

You will collaborate with data scientists and ML engineers, implement data management, feature stores and model versioning, and ensure performance, security, and cost efficiency of the platforms.