Remote MLOps Engineer — Build Scalable AI Pipelines

Placements24; Polokwane; Hybrid; ZAR 700,000 - 1,100,000; Full time

Benefits offered by this job

Fully remote

Flexible scheduling

Professional development budget

Competitive salary

Job summary

Placements24 is seeking an AI Operations Engineer (MLOps) to join a fully remote, high-performing team. Design and maintain infrastructure and pipelines for efficient development, deployment, and monitoring of ML models to ensure reliability and scalability.

You will build CI/CD for ML, manage training and deployment infrastructure, monitor performance and drift, and automate workflows while upholding security and compliance across the ML lifecycle.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field.
• 3+ years of experience in DevOps, SRE, or MLOps roles.
• Proficiency with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
• Experience with CI/CD tools (e.g., Jenkins, GitLab CI, GitHub Actions).
• Familiarity with scripting languages (e.g., Python, Bash) and infrastructure-as-code tools (e.g., Terraform, Ansible).
• Understanding of machine learning concepts and workflows.

Responsibilities

• Design, implement, and manage robust CI/CD pipelines for machine learning models.
• Develop and maintain infrastructure for training, deploying, and serving ML models at scale.
• Implement monitoring solutions to track model performance, drift, and operational health in production.
• Automate ML workflows, data pipelines, and model retraining processes.
• Collaborate with data scientists and software engineers to troubleshoot and resolve operational issues.
• Ensure security, compliance, and best practices are followed throughout the ML lifecycle.

Skills

CI/CD for ML

Cloud platforms

Containerization

Python scripting

IaC

ML concepts

Education

Bachelor's degree in CS/Engineering

Tools

Terraform

Ansible

GitHub Actions

Docker

Kubernetes

GitLab CI

Job description

Placements24 is seeking an AI Operations Engineer (MLOps) to join a fully remote, high-performing team. Design and maintain infrastructure and pipelines for efficient development, deployment, and monitoring of ML models to ensure reliability and scalability.

You will build CI/CD for ML, manage training and deployment infrastructure, monitor performance and drift, and automate workflows while upholding security and compliance across the ML lifecycle.