MLOps Engineer: Build Scalable AI Deployments

Placements24; Gqeberha; On-site; ZAR 600,000 - 860,000; Full time

Benefits offered by this job

Competitive salary

Career advancement

Collaborative team

On-site role

Job summary

Placements24 in Port Elizabeth is seeking a skilled MLOps Engineer to bridge ML development and production deployment. You will design and maintain CI/CD pipelines, build scalable infrastructure for training, deployment, and monitoring of ML models, and automate end-to-end ML workflows.

The role requires 3+ years in software engineering or DevOps with an MLOps focus, plus strong scripting (Python/Bash) and IaC (Terraform/Ansible) skills.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or related field.
• 3+ years in software engineering or DevOps with a focus on MLOps.
• Proficiency in Python and Bash scripting and IaC tools (Terraform, Ansible).
• Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
• Strong understanding of CI/CD principles and practices.

Responsibilities

• Design, implement, and maintain CI/CD pipelines for ML models.
• Develop and manage infrastructure for training, deploying, and monitoring ML models at scale.
• Automate ML workflows: data ingestion, feature engineering, model training and evaluation.
• Implement robust monitoring, logging, and alerting for ML production.
• Collaborate with data scientists and software engineers to ensure smooth integration.
• Troubleshoot and resolve issues in the ML production environment.

Skills

MLOps

CI/CD principles

Scripting (Python/Bash)

Education

Bachelor's degree in Computer Science, Engineering, or related field

Tools

Terraform

Ansible

Docker

Kubernetes

AWS

Azure

GCP

Job description

Placements24 in Port Elizabeth is seeking a skilled MLOps Engineer to bridge ML development and production deployment. You will design and maintain CI/CD pipelines, build scalable infrastructure for training, deployment, and monitoring of ML models, and automate end-to-end ML workflows.

The role requires 3+ years in software engineering or DevOps with an MLOps focus, plus strong scripting (Python/Bash) and IaC (Terraform/Ansible) skills.