Mlops Engineer

Network Contracting; Johannesburg; On-site; ZAR 900,000 - 1,500,000; Full time

Job summary

Network Contracting seeks an experienced MLOps Engineer to design, implement, and maintain end-to-end ML deployment pipelines in a modern cloud environment. You will automate training, testing, deployment, and monitoring, while building scalable ML infrastructure and ensuring production reliability.

You will collaborate with data scientists and DevOps teams, applying CI/CD best practices and IaC to govern ML lifecycle, security, and performance across platforms.

Qualifications

• Bachelor's degree in a relevant field.
• 3+ years in MLOps, DevOps, Data Engineering, or ML Engineering.
• Strong Python and scripting experience.
• Hands-on with Azure, AWS, or Google Cloud.
• Experience with Docker and Kubernetes.
• Knowledge of CI/CD and Infrastructure as Code.
• Experience with ML lifecycle tools such as MLflow, Kubeflow, Airflow.
• Familiarity with ML production deployment processes.
• Strong troubleshooting, automation, and problem-solving skills.

Responsibilities

• Design, implement, and maintain end-to-end ML deployment pipelines.
• Automate model training, testing, deployment, and monitoring processes.
• Build and manage scalable cloud-based ML infrastructure.
• Monitor model performance and ensure reliability in production environments.
• Implement CI/CD best practices for ML workflows.
• Collaborate with Data Scientists to operationalise ML models.
• Manage model versioning, governance, and lifecycle processes.
• Ensure security, scalability, and performance of AI platforms.

Skills

Python

Scripting

Cloud platforms

Docker

Kubernetes

CI/CD

Infrastructure as Code

MLflow

Kubeflow

Airflow

Education

Bachelor's Degree in Computer Science, Engineering, Data Science, or a related field

Tools

Docker

Kubernetes

MLflow

Kubeflow

Airflow

Job description

Our client is an innovative organisation committed to leveraging data and AI to drive business transformation. They are seeking an experienced MLOps Engineer to build and maintain robust machine learning infrastructure, ensuring models are deployed efficiently, monitored effectively, and continuously improved.

Working closely with Data Scientists, Data Engineers, and DevOps teams, you will help bring AI solutions from experimentation to production.

What's in It for You?

• Work on cutting-edge AI and Machine Learning initiatives.
• Collaborate with highly skilled technology professionals.
• Exposure to modern cloud, automation, and MLOps technologies.
• Opportunities for career growth and continuous learning.
• Competitive salary and benefits package.
• Dynamic and innovation-focused work environment.

Key Responsibilities

• Design, implement, and maintain end-to-end ML deployment pipelines.
• Automate model training, testing, deployment, and monitoring processes.
• Build and manage scalable cloud-based ML infrastructure.
• Monitor model performance and ensure reliability in production environments.
• Implement CI/CD best practices for machine learning workflows.
• Collaborate with Data Scientists to operationalise machine learning models.
• Manage model versioning, governance, and lifecycle processes.
• Ensure security, scalability, and performance of AI platforms.

Experience & Skills of the Ideal Candidate

• Bachelor's Degree in Computer Science, Engineering, Data Science, or a related field.
• 3+ years of experience in MLOps, DevOps, Data Engineering, or Machine Learning Engineering.
• Strong experience with Python and scripting languages.
• Hands-on experience with cloud platforms such as Azure, AWS, or Google Cloud.
• Experience with containerisation technologies such as Docker and Kubernetes.
• Knowledge of CI/CD pipelines and Infrastructure as Code.
• Experience with ML lifecycle tools such as MLflow, Kubeflow, Airflow, or similar.
• Familiarity with machine learning frameworks and production deployment processes.
• Strong troubleshooting, automation, and problem-solving skills.