Hybrid AI Infrastructure Engineer - Cloud & MLOps Specialist

Placements24; Stellenbosch; Hybrid; ZAR 900,000 - 1,300,000; Full time

Benefits offered by this job

Competitive salary

Hybrid work arrangement

Professional development opportunities

Advanced training

Collaborative team environment

Impactful AI infrastructure

Job summary

Placements24 in Stellenbosch seeks an AI Infrastructure Engineer to design, build, and optimize scalable AI/ML infrastructure across cloud platforms. You will implement CI/CD pipelines for AI models and infrastructure deployment, while optimizing compute and storage for large datasets and model training.

The role requires strong containerization with Docker/Kubernetes, scripting in Python or Bash, and familiarity with MLOps and IaC tools such as Terraform and Ansible.

Qualifications

• Bachelor's degree in a technical field.
• 3+ years of experience in infrastructure engineering.
• Strong experience with containerization (Docker, Kubernetes).
• Scripting proficiency (Python, Bash).
• Familiarity with MLOps principles and tools.
• Experience with infrastructure as code (Terraform, Ansible).

Responsibilities

• Design, implement, and manage scalable AI/ML infrastructure on cloud platforms.
• Develop and maintain CI/CD pipelines for AI models and infrastructure deployment.
• Optimize compute and storage resources for large-scale data processing and model training.
• Implement monitoring, logging, and alerting for AI infrastructure components.
• Troubleshoot infrastructure issues affecting AI development and deployment.
• Collaborate with ML engineers and data scientists to understand infrastructure needs.

Skills

Python

Bash

CI/CD

MLOps

Education

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

Tools

Docker

Kubernetes

Terraform

Ansible

Job description

Placements24 in Stellenbosch seeks an AI Infrastructure Engineer to design, build, and optimize scalable AI/ML infrastructure across cloud platforms. You will implement CI/CD pipelines for AI models and infrastructure deployment, while optimizing compute and storage for large datasets and model training.

The role requires strong containerization with Docker/Kubernetes, scripting in Python or Bash, and familiarity with MLOps and IaC tools such as Terraform and Ansible.