MLOps Engineer: Scale AI Pipelines & CI/CD

Placements24; Soweto; Hybrid; ZAR 700,000 - 950,000; Full time

Benefits offered by this job

Competitive salary

Professional development

Collaborative environment in Soweto

Exposure to cutting-edge AI tech

Deployment of advanced AI solutions

Job summary

Placements24 in Soweto is seeking a skilled Machine Learning Ops (MLOps) Engineer to bridge ML development and production deployment, ensuring AI models are built, deployed, monitored, and maintained at scale.

You will collaborate with data scientists and software engineers, design robust CI/CD pipelines, manage experiments and data/model versioning, and contribute to secure, high‑performing ML infrastructure across the Gauteng region.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or related field.
• 2+ years in MLOps/DevOps focusing on ML systems.
• Proficiency in Python and scripting.
• Experience with cloud platforms and containers.
• Familiarity with ML frameworks and MLOps tools.

Responsibilities

• Design, build, and maintain scalable and reliable MLOps pipelines for CI/CD of machine learning models.
• Automate model training, deployment, and monitoring processes.
• Implement tools and infrastructure for managing ML experiments, data versioning, and model versioning.
• Collaborate with data scientists to optimize models for production environments.
• Monitor deployed models for performance, drift, and potential issues, implementing necessary adjustments.
• Ensure the security, scalability, and efficiency of ML infrastructure.

Skills

Python

Cloud platforms

CI/CD

ML systems

Software engineering

Education

Bachelor's degree in CS/Engineering

Tools

Docker

Kubernetes

MLflow

Kubeflow

TensorFlow

PyTorch

Git

Job description

Placements24 in Soweto is seeking a skilled Machine Learning Ops (MLOps) Engineer to bridge ML development and production deployment, ensuring AI models are built, deployed, monitored, and maintained at scale.

You will collaborate with data scientists and software engineers, design robust CI/CD pipelines, manage experiments and data/model versioning, and contribute to secure, high‑performing ML infrastructure across the Gauteng region.