Hybrid MLOps Engineer in Soweto – AI Deploy & CI/CD

Placements24; Soweto; Hybrid; ZAR 900,000 - 1,300,000; Full time

Benefits offered by this job

Hybrid role

Soweto based

Professional development opportunities

Retirement plan

Job summary

Placements24 is seeking a skilled MLOps Engineer to join our Soweto, Gauteng team. You will bridge model development and production, building scalable pipelines, automating ML workflows, and enforcing CI/CD practices.

The role requires collaboration with data scientists and software engineers to deliver reliable ML systems. Ideal candidates have 3+ years in MLOps/DevOps, strong Python and Shell scripting skills, and hands-on experience with Docker, Kubernetes, and cloud ML services.

Qualifications

• Bachelor's degree in Computer Science, Software Engineering, or a related technical field.
• 3+ years of experience in MLOps, DevOps, or a related role.
• Strong Python programming and shell scripting skills.
• Experience with cloud platforms (AWS, Azure, GCP) and ML services.

Responsibilities

• Design, build, and maintain scalable MLOps pipelines for automated model training, deployment, and monitoring.
• Implement CI/CD practices for machine learning models.
• Develop and manage infrastructure for ML model deployment, including Docker and Kubernetes.
• Monitor ML model performance in production and plan retraining strategies.
• Collaborate with data scientists and software engineers to streamline the ML lifecycle.
• Ensure reliability, scalability, and security of ML systems.
• Automate data validation, model testing, and deployment processes.
• Stay current with emerging MLOps tools and best practices.

Skills

Python

Shell scripting

Problem solving

Communication

Education

Bachelor's degree in Computer Science or Software Engineering

Tools

Docker

Kubernetes

Jenkins

GitLab CI

GitHub Actions

Terraform

Ansible

Job description

Placements24 is seeking a skilled MLOps Engineer to join our Soweto, Gauteng team. You will bridge model development and production, building scalable pipelines, automating ML workflows, and enforcing CI/CD practices.

The role requires collaboration with data scientists and software engineers to deliver reliable ML systems. Ideal candidates have 3+ years in MLOps/DevOps, strong Python and Shell scripting skills, and hands-on experience with Docker, Kubernetes, and cloud ML services.