Machine Learning Operations (MLOps) Engineer

Placements24; Sandton; Hybride; ZAR 900 000 - 1 300 000; Plein temps

Avantages offerts par ce poste

Health insurance

Retirement contributions

Generous paid time off

Professional development

Résumé du poste

Placements24 in Sandton, Gauteng, seeks an experienced MLOps Engineer to streamline ML deployment, monitoring, and maintenance in production. The role combines AI operations with collaboration across data science and software teams in a hybrid work setting.

The candidate should have a strong background in MLOps, DevOps, and cloud ML services, with proficiency in Python, Docker, Kubernetes, and CI/CD tooling. A CS/Engineering degree is preferred for this position.

Qualifications

• Experience in MLOps, DevOps, or ML systems.
• Hands-on experience with cloud platforms (AWS, Azure, GCP) and their ML services.
• Proficiency in Python scripting and programming.
• Experience with Docker and Kubernetes for ML deployments.
• Familiarity with CI/CD tools (Jenkins, GitLab CI, GitHub Actions).
• Knowledge of infrastructure as code (Terraform, CloudFormation).
• Strong problem-solving and collaboration skills.

Responsabilités

• Design, implement, and manage MLOps pipelines for training, deployment, and monitoring.
• Develop infrastructure for deploying and serving ML models at scale.
• Apply CI/CD practices to ML models across environments.
• Monitor model performance, drift, and retraining needs.
• Collaborate with data scientists and engineers to optimize production ML workflows.
• Automate ML infrastructure including containers and cloud resources.
• Manage model versioning, artifacts, and experiment tracking.
• Ensure security and reliability of ML production systems.

Connaissances

MLOps

DevOps

Python

Docker

Kubernetes

CI/CD

Cloud platforms

Formation

CS/Engineering degree

Outils

Docker

Kubernetes

Terraform

CloudFormation

Jenkins

GitLab CI

GitHub Actions

AWS

Azure

GCP

Description du poste

About the Role

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.

Key Responsibilities

• 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.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Proven experience in MLOps, DevOps, 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, GitLab CI, GitHub Actions).
• Understanding of machine learning concepts and model lifecycle management.
• Experience with infrastructure as code (IaC) tools like Terraform or CloudFormation is a plus.
• Strong problem-solving and analytical skills.
• Excellent communication and collaboration skills for working in a hybrid team.

Benefits

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.