MLOps Specialist: AI Deployment, Cloud CI/CD & Kubernetes

Placements24; East London; On-site; ZAR 700,000 - 900,000; Full time

Job summary

Placements24 is seeking a dedicated MLOps Specialist to join their technology infrastructure team in East London. This role focuses on deploying, monitoring, and maintaining ML models in production, bridging data science and operations to ensure reliable AI systems.

You will implement CI/CD pipelines, automate deployments, and scale ML workflows with Docker and Kubernetes, collaborating with data scientists and engineers to improve model performance and stability.

Qualifications

• Bachelor's degree in CS, Engineering or a related technical field.
• 3+ years in software engineering, DevOps, or MLOps.
• Experience with AWS, Azure or GCP and their MLOps services.
• Experience with Docker and Kubernetes.
• Strong scripting in Python or Bash and CI/CD tools.
• Understanding of ML concepts and model lifecycles.

Responsibilities

• Implement and manage CI/CD pipelines for ML models and infrastructure.
• Automate deployment, testing, and monitoring of ML models in production.
• Develop and maintain scalable infrastructure for ML training and inference.
• Collaborate with data scientists and engineers to improve model performance.
• Implement robust logging, monitoring and alerting for ML apps.
• Manage containerization and orchestration for ML workloads.

Skills

CI/CD

Docker

Kubernetes

Python

Cloud platforms

MLOps

DevOps

Scripting

Model lifecycles

Logging & monitoring

Education

Bachelor's degree

Tools

CI/CD tools

Docker

Kubernetes

Job description

Placements24 is seeking a dedicated MLOps Specialist to join their technology infrastructure team in East London. This role focuses on deploying, monitoring, and maintaining ML models in production, bridging data science and operations to ensure reliable AI systems.

You will implement CI/CD pipelines, automate deployments, and scale ML workflows with Docker and Kubernetes, collaborating with data scientists and engineers to improve model performance and stability.