Machine Learning Engineer - MLOps

Placements24; Noord-Kaap; On-site; ZAR 600,000 - 1,000,000; Full time

Benefits offered by this job

Competitive salary

Health and retirement benefits

Growth and training opportunities

Collaborative team in Kimberley

Job summary

Placements24 is hiring a Machine Learning Engineer with a specialization in MLOps to join our Kimberley team. The role focuses on building scalable ML deployment and monitoring pipelines, enabling rapid iteration and reliable production systems.

You will work closely with data scientists and software engineers to operationalize models, implement CI/CD for ML workflows, and ensure ongoing performance and reliability of AI solutions.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field.
• 3+ years of software engineering or DevOps with a focus on MLOps or ML infrastructure.
• Proficiency in Python scripting and containerization (Docker, Kubernetes).
• Experience with cloud platforms (AWS, Azure, GCP) and their ML services.

Responsibilities

• Design, build, and maintain robust MLOps pipelines for model training, deployment, and monitoring.
• Implement automation for CI/CD processes tailored for ML workflows.
• Develop tools and infrastructure for model versioning, testing, and deployment.
• Monitor deployed models for performance degradation, drift, and operational issues.
• Collaborate with data scientists to operationalize their models efficiently.

Skills

Python

MLOps

Docker

Kubernetes

Cloud ML services

Education

Bachelors in CS/Engineering

Tools

Docker

Kubernetes

AWS/Azure/GCP

Job description

About the Role

Our client is seeking a skilled Machine Learning Engineer with a specialization in MLOps to join their team in Kimberley . This role is critical for ensuring the smooth, scalable, and reliable deployment and operation of machine learning models in production. You will build and maintain the infrastructure and tools that enable rapid iteration and deployment of ML models, working closely with data scientists and software engineers. This position offers a unique opportunity to work at the intersection of machine learning and software engineering, contributing to the operational excellence of advanced AI systems.

Key Responsibilities

• Design, build, and maintain robust MLOps pipelines for model training, deployment, and monitoring.
• Implement automation for CI/CD processes tailored for machine learning workflows.
• Develop tools and infrastructure for model versioning, testing, and deployment.
• Monitor deployed models for performance degradation, drift, and operational issues.
• Collaborate with data scientists to operationalize their models efficiently and effectively.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field.
• 3+ years of experience in software engineering or DevOps, with a focus on MLOps or machine learning infrastructure.
• Proficiency in scripting languages like Python and experience with containerization technologies (Docker, Kubernetes).
• Experience with cloud platforms (AWS, Azure, GCP) and their ML services.
• Strong understanding of machine learning concepts and the ML lifecycle.

Benefits

• Competitive salary and performance incentives.
• Comprehensive health and retirement benefits.
• Opportunities for professional growth and training in emerging MLOps practices.
• A collaborative team environment in Kimberley .
• Contribute to building scalable and reliable AI systems.