MLOps Engineer: AI Infrastructure & Scalable Deployments

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

Benefits offered by this job

Medical aid

Life insurance

Retirement fund contributions

Training & certifications

Job summary

Placements24 in Klerksdorp, North West is seeking an experienced MLOps Engineer to establish and manage ML infrastructure on-site. You will design CI/CD pipelines, automate ML workflows, and ensure scalable, reliable AI systems.

Collaboration with data scientists and engineers is essential for lifecycle management and deployment strategies. The role emphasizes automation, monitoring, and cost-efficient ML infrastructure, with opportunities to advance in a cutting-edge AI environment.

Qualifications

• Bachelor's degree in CS, Engineering or related field.
• Proven experience in DevOps or MLOps engineering.
• Experience with ML lifecycle and frameworks (TensorFlow, PyTorch).
• Strong scripting (Python, Bash) and IaC (Terraform, Ansible).

Responsibilities

• Design, build, and maintain CI/CD pipelines for ML models.
• Automate training, testing, deployment of ML models.
• Monitor model performance and infrastructure health.
• Manage ML inference infrastructure and serving.
• Collaborate with data scientists and engineers on model lifecycle.
• Optimize infrastructure for performance and cost.
• Document MLOps processes and tools.

Skills

DevOps

MLOps

CI/CD

Python

Docker

Kubernetes

TensorFlow

PyTorch

Terraform

Ansible

Education

Bachelor's degree in Computer Science or related

Tools

GitHub Actions

Jenkins

GitLab CI

Terraform

Docker

Kubernetes

Job description

Placements24 in Klerksdorp, North West is seeking an experienced MLOps Engineer to establish and manage ML infrastructure on-site. You will design CI/CD pipelines, automate ML workflows, and ensure scalable, reliable AI systems.

Collaboration with data scientists and engineers is essential for lifecycle management and deployment strategies. The role emphasizes automation, monitoring, and cost-efficient ML infrastructure, with opportunities to advance in a cutting-edge AI environment.