MLOps Engineer: Cloud ML Pipelines & CI/CD

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

Benefits offered by this job

Competitive salary

Cutting-edge MLOps tech

Diverse projects

Continuous learning

Collaborative culture

Job summary

Placements24 in Sandton, South Africa, is seeking an experienced MLOps Engineer to bridge ML model development and production deployment. You will design and maintain scalable ML pipelines, ensure reliability, and collaborate with data scientists and software engineers to optimize the ML lifecycle.

The role focuses on cloud-based infrastructure, Docker and Kubernetes, and CI/CD automation, with opportunities to work on cutting-edge ML projects and advance your skills in a dynamic, collaborative

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field.
• Proven experience in MLOps, DevOps, or a related field with a focus on machine learning.
• Strong understanding of cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
• Proficiency in Python scripting and experience with ML frameworks.
• Experience with CI/CD tools, monitoring systems, and infrastructure as code principles.

Responsibilities

• Design, build, and maintain scalable CI/CD pipelines for machine learning models.
• Implement and manage infrastructure for training, deploying, and monitoring ML models in production.
• Automate ML workflows, including data validation, model training, deployment, and performance monitoring.
• Collaborate with data scientists and software engineers to streamline the ML lifecycle.
• Troubleshoot and resolve issues related to ML systems in production, ensuring high availability and performance.

Skills

MLOps

DevOps

CI/CD

Python scripting

Education

Bachelor's degree in Computer Science, Engineering

Tools

Docker

Kubernetes

AWS

Azure

GCP

Terraform

Job description

Placements24 in Sandton, South Africa, is seeking an experienced MLOps Engineer to bridge ML model development and production deployment. You will design and maintain scalable ML pipelines, ensure reliability, and collaborate with data scientists and software engineers to optimize the ML lifecycle.

The role focuses on cloud-based infrastructure, Docker and Kubernetes, and CI/CD automation, with opportunities to work on cutting-edge ML projects and advance your skills in a dynamic, collaborative