Senior MLOps Engineer: Scale AI Pipelines & Cloud Infra

Placements24; Pietermaritzburg; Hybrid; ZAR 1,200,000 - 2,000,000; Full time

Benefits offered by this job

Health insurance

Paid time off

Professional development

Pension plan

Access to AI tools

Job summary

Placements24 in Pietermaritzburg, KwaZulu-Natal, seeks an experienced Senior AI/ML Operations Engineer (MLOps) to design, automate, and scale production ML infrastructure. You will own CI/CD for ML, deploy pipelines, and ensure reliable, cost-effective operation across cloud platforms.

Collaborating with data scientists and software engineers, you will implement robust monitoring, security, and governance while optimizing workflows.

Qualifications

• Requires a degree in Computer Science, Engineering or related field.
• 5+ years in software engineering, DevOps or related roles with MLOps focus.
• Proven experience building and managing ML CI/CD pipelines.

Responsibilities

• Design, build, and maintain scalable MLOps pipelines across the ML lifecycle.
• Automate deployment, monitoring, and management of ML models in production.
• Develop infrastructure for training, testing, and deploying ML models.
• Collaborate with data scientists and ML engineers on deployment needs.
• Implement CI/CD best practices for ML projects.
• Monitor ML system performance and address issues.
• Manage cloud infrastructure (AWS/Azure/GCP) for ML workloads.
• Ensure security, reliability, and cost-effectiveness of operations.
• Document MLOps processes and procedures.

Skills

CI/CD for ML

Cloud platforms

Docker & Kubernetes

ML frameworks

Python

IaC (Terraform/Ansible)

MLOps

Monitoring & observability

CI/CD pipelines for ML

Education

Bachelor's or Master's in CS/Engineering

Tools

Docker

Kubernetes

Terraform

Ansible

TensorFlow

PyTorch

Scikit-learn

Job description

Placements24 in Pietermaritzburg, KwaZulu-Natal, seeks an experienced Senior AI/ML Operations Engineer (MLOps) to design, automate, and scale production ML infrastructure. You will own CI/CD for ML, deploy pipelines, and ensure reliable, cost-effective operation across cloud platforms.

Collaborating with data scientists and software engineers, you will implement robust monitoring, security, and governance while optimizing workflows.