AI Platform Engineer – Hybrid & Scale ML Infra

Placements24; Upington; Hybrid; ZAR 600,000 - 900,000; Full time

Benefits offered by this job

Competitive salary

Hybrid work model

Cutting-edge AI tech

Professional development

Innovative environment

Job summary

Placements24 is seeking an AI Platform Engineer to design, implement, and scale AI/ML infrastructure across cloud environments. You will work on scalable platforms, data pipelines, and MLOps workflows to enable data scientists and engineers to train and deploy models efficiently.

The role requires 3+ years in software engineering or DevOps with a focus on AI/ML infrastructure, strong scripting skills, and expertise with AWS/Azure/GCP, Docker and Kubernetes. A hybrid work model is offered in SA.

Qualifications

• Bachelor's degree in CS, Engineering or related field.
• 3+ years in software engineering or DevOps with a focus on AI/ML infra.
• Experience with AWS, Azure or GCP and Docker/Kubernetes.
• Proficiency in Python or Bash and familiarity with IaC tools.
• Understanding of data science and ML workflows.

Responsibilities

• Design, build, and maintain scalable AI/ML infrastructure and platforms.
• Develop and manage CI/CD pipelines for AI model deployment (MLOps).
• Implement and optimize data pipelines for AI workloads, ensuring data quality.
• Provide engineering support for data scientists and ML engineers, troubleshooting platform issues.
• Automate infrastructure provisioning, configuration, and management.
• Ensure security, reliability, and performance of the AI platform.

Skills

AI/ML infrastructure

Scripting

CI/CD

Data science workflows

Education

Bachelor's degree in CS/Engineering or related field

Tools

AWS

Azure

GCP

Docker

Kubernetes

Infrastructure-as-code (IaC)

MLOps tools

Job description

Placements24 is seeking an AI Platform Engineer to design, implement, and scale AI/ML infrastructure across cloud environments. You will work on scalable platforms, data pipelines, and MLOps workflows to enable data scientists and engineers to train and deploy models efficiently.

The role requires 3+ years in software engineering or DevOps with a focus on AI/ML infrastructure, strong scripting skills, and expertise with AWS/Azure/GCP, Docker and Kubernetes. A hybrid work model is offered in SA.