Senior MLOps Engineer - Remote AI Deployment & Scale

Placements24; Soweto; Hybrid; ZAR 1,000,000 - 1,800,000; Full time

Benefits offered by this job

Medical aid

Retirement fund

Professional development opportunities

Fully remote work

Job summary

Placements24, a dynamic AI-focused company, seeks a Senior AI Engineer specializing in MLOps to build and maintain scalable ML systems. This fully remote role allows you to contribute from anywhere, with operations near Soweto, Gauteng.

You will design end-to-end ML pipelines, implement CI/CD for ML workloads, manage model versioning, and collaborate with data scientists to productionize models while ensuring security and reliability across cloud platforms.

Qualifications

• 6+ years in software engineering or DevOps with a focus on MLOps.
• Experience deploying ML models to production on cloud platforms.
• Proficient in Python and scripting languages.
• Hands-on with AWS SageMaker, Azure ML, GCP.
• Familiar with Docker and Kubernetes.
• Knowledge of CI/CD tools (Jenkins, GitLab CI, GitHub Actions).

Responsibilities

• Design and manage end-to-end MLOps pipelines for training, testing, deployment, and monitoring.
• Develop CI/CD infrastructure for ML workflows.
• Implement model versioning, experiment tracking, and reproducibility.
• Set up infrastructure for training and serving ML models on cloud platforms.
• Monitor production models and retraining strategies.
• Collaborate with data scientists to optimize models for production.
• Develop logging, alerting, and reporting for ML systems.
• Automate data pipelines and feature stores for ML development.
• Ensure security, scalability, and reliability of ML infrastructure.
• Stay current with MLOps best practices and document processes for the team in Soweto.

Skills

MLOps

Python

Cloud platforms

Docker & Kubernetes

CI/CD

Education

Bachelor's/Master's in CS/Engineering

Tools

MLflow

Kubeflow

DVC

GitHub Actions

Job description

Placements24, a dynamic AI-focused company, seeks a Senior AI Engineer specializing in MLOps to build and maintain scalable ML systems. This fully remote role allows you to contribute from anywhere, with operations near Soweto, Gauteng.

You will design end-to-end ML pipelines, implement CI/CD for ML workloads, manage model versioning, and collaborate with data scientists to productionize models while ensuring security and reliability across cloud platforms.