Machine Learning Operations; MLOps) Engineer

Our client, a leader in AI and emerging technologies, is looking for a skilled Machine Learning Operations (MLOps) Engineer to join their team in Sandton, Gauteng, ZA . This role is essential for streamlining the deployment, monitoring, and maintenance of machine learning models in production environments. You will bridge the gap between data science and operations, ensuring our AI solutions are reliable, scalable, and efficient.

This position offers a hybrid work arrangement, blending office collaboration with remote flexibility.

• Design, implement, and manage robust MLOps pipelines for automated model training, testing, deployment, and monitoring.
• Develop and maintain infrastructure for deploying and serving ML models at scale.
• Implement continuous integration and continuous delivery (CI/CD) practices for ML models.
• Monitor model performance in production, identify drift, and implement retraining strategies.
• Collaborate with data scientists and software engineers to optimize models for production environments.
• Manage and automate the infrastructure required for ML workflows, including cloud resources and containerization (Docker, Kubernetes).
• Implement strategies for model versioning, artifact management, and experiment tracking.
• Ensure the reliability, scalability, and security of ML production systems.
• Troubleshoot and resolve issues related to ML model deployment and performance.
  
  Stay current with MLOps best practices and emerging tools and technologies.

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Proven experience in MLOps, Dev Ops, or software engineering with a focus on ML systems.
• Hands-on experience with cloud platforms (AWS, Azure, GCP) and their ML services.
• Proficiency in scripting and programming languages such as Python.
• Experience with containerization technologies (Docker, Kubernetes).
• Familiarity with CI/CD tools (e.g., Jenkins, Git Lab CI, Git Hub Actions).
• Understanding of machine learning concepts and model lifecycle management.
• Experience with infrastructure as code (IaC) tools like Terraform or Cloud Formation is a plus.
• Strong problem-solving and analytical skills.
• Excellent communication and collaboration skills for working in a hybrid team.

Our client offers a competitive salary, performance-based incentives, and a comprehensive benefits package including health insurance, retirement contributions, and generous paid time off. The hybrid work model provides flexibility and promotes work-life balance. Employees have access to professional development resources and opportunities to work on cutting-edge AI projects. Join a collaborative team dedicated to advancing the field of machine learning operations.