AI/ML Platform Engineer - Hybrid in Paarl, Growth

Placements24; Paarl; Hybrid; ZAR 720,000 - 1,100,000; Full time

Benefits offered by this job

Competitive salary

Health benefits

Learning opportunities

Hybrid work model

Paarl location experience

Job summary

Placements24 in Paarl, Western Cape seeks an innovative AI/ML Platform Engineer to join our growing tech team. You will build and maintain an infrastructure that enables data scientists to develop, train, and deploy ML models efficiently in cloud environments.

The role focuses on scalable, reliable platform design, MLOps tooling, and containerization with Docker and Kubernetes. You will collaborate with engineers and scientists to meet platform needs while maintaining security and performance.

Qualifications

• Bachelor's degree in CS/Engineering or a related technical field.
• Experience in platform engineering, DevOps or SRE for AI/ML infra.
• Proficiency with cloud platforms and IaC tools.
• Experience with Docker and Kubernetes.

Responsibilities

• Design, build, and manage AI/ML platform infrastructure on cloud environments (AWS/Azure/GCP).
• Implement and maintain MLOps tools for CI/CD, model versioning, monitoring, and deployment.
• Develop and manage containerization solutions (Docker, Kubernetes) for ML workloads.
• Automate infrastructure provisioning with Terraform or Ansible.
• Collaborate with data scientists and ML engineers to understand platform needs.
• Ensure scalability, reliability, and security of the AI/ML platform.
• Troubleshoot and resolve platform performance issues.

Skills

MLOps

Problem-solving

Teamwork

Communication

Education

Bachelor's degree in Computer Science or Engineering

Tools

Docker

Kubernetes

Terraform

Ansible

TensorFlow

PyTorch

AWS

Azure

GCP

Job description

Placements24 in Paarl, Western Cape seeks an innovative AI/ML Platform Engineer to join our growing tech team. You will build and maintain an infrastructure that enables data scientists to develop, train, and deploy ML models efficiently in cloud environments.

The role focuses on scalable, reliable platform design, MLOps tooling, and containerization with Docker and Kubernetes. You will collaborate with engineers and scientists to meet platform needs while maintaining security and performance.