MLOps Engineer: Build & Scale Production AI Pipelines

Placements24; Benoni; Hybride; ZAR 600 000 - 900 000; Plein temps

Avantages offerts par ce poste

Medical insurance

Retirement benefits

Paid time off

Career development

Hybrid work environment

Résumé du poste

Placements24 seeks an AI/ML Operations Engineer (MLOps) to bridge model development and production deployment in Benoni, Gauteng. You will build and maintain automated ML pipelines, manage CI/CD, and ensure scalable, secure ML systems in production.

Requirements include a CS/engineering degree and 2+ years in MLOps or related roles, with strong Python, cloud, Docker, and Kubernetes experience. A hybrid work setup in Benoni is offered, with growth opportunities in AI initiatives.

Qualifications

• Requires a Bachelor's degree in CS/Engineering or related field.
• 2+ years in MLOps/DevOps or related role with ML focus.
• Proficient in Python scripting.
• Experience with cloud platforms and ML services.
• Familiarity with containerization and orchestration (Docker/Kubernetes).
• Knowledge of Terraform/Ansible is desirable.

Responsabilités

• Design and maintain automated MLOps pipelines for model training and deployment.
• Implement infra and tools to support ML lifecycle.
• Develop model versioning, testing, and rollback strategies.
• Set up CI/CD for ML models and monitor production performance.
• Collaborate with data scientists to ensure production readiness and scalability.
• Integrate ML systems into existing DevOps processes and secure operations.
• Automate data preprocessing and feature engineering pipelines.

Connaissances

Python

Cloud platforms

Docker

Kubernetes

CI/CD tools

Terraform/Ansible

Formation

Bachelor's degree in CS/Engineering

Outils

Jenkins

GitLab CI

GitHub Actions

Docker

Kubernetes

Description du poste

Placements24 seeks an AI/ML Operations Engineer (MLOps) to bridge model development and production deployment in Benoni, Gauteng. You will build and maintain automated ML pipelines, manage CI/CD, and ensure scalable, secure ML systems in production.

Requirements include a CS/engineering degree and 2+ years in MLOps or related roles, with strong Python, cloud, Docker, and Kubernetes experience. A hybrid work setup in Benoni is offered, with growth opportunities in AI initiatives.