AI Platform Engineer — Cloud & MLOps Pipelines

Placements24; Noord-Kaap; On-site; ZAR 600,000 - 900,000; Full time

Benefits offered by this job

Salary + bonus

Advanced AI infrastructure

Health benefits

PTO & vacation

Professional growth

Job summary

Placements24 is looking for an AI Platform Engineer to join our Kimberley team to design, build, and scale AI/ML infrastructure. You will create robust data pipelines, manage ML workflows, and ensure reliable AI development and deployment environments.

The role collaborates with data scientists and ML engineers to support operational needs, leveraging cloud platforms and containerization in a cutting-edge technical culture.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related technical field.
• 3+ years of experience in platform engineering, DevOps, or MLOps.
• Proficiency with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
• Experience with infrastructure as code tools (Terraform, Ansible).
• Familiarity with data processing frameworks (Spark, Flink) and ML libraries.

Responsibilities

• Design, build, and maintain scalable AI/ML infrastructure and platforms.
• Develop and optimize data pipelines for ingestion, processing, and storage of large datasets.
• Implement and manage ML workflow orchestration tools (e.g., Kubeflow, MLflow).
• Ensure the performance, reliability, and security of AI development and production environments.
• Collaborate with data scientists and ML engineers to support their operational needs.

Skills

Platform engineering

DevOps

MLOps

Cloud platforms

Kubernetes

Docker

Terraform

Ansible

Spark

Flink

ML libraries

Education

Bachelor's degree

Tools

Kubeflow

MLflow

Terraform

Ansible

Docker

Kubernetes

Spark

Flink

Job description

Placements24 is looking for an AI Platform Engineer to join our Kimberley team to design, build, and scale AI/ML infrastructure. You will create robust data pipelines, manage ML workflows, and ensure reliable AI development and deployment environments.

The role collaborates with data scientists and ML engineers to support operational needs, leveraging cloud platforms and containerization in a cutting-edge technical culture.