Machine Learning Operations (MLOps) Engineer

Placements24; Benoni; Hybrid; ZAR 700,000 - 1,100,000; Full time

Benefits offered by this job

Competitive salary

Hybrid work model

Access to advanced MLOps technologies

Career growth opportunities

Job summary

Placements24 is seeking a skilled MLOps Engineer to join our Benoni team. You will design and maintain CI/CD pipelines, build scalable infrastructure for training, deployment, and monitoring of ML models, and collaborate with data scientists and software engineers to operationalize models.

You will work in a hybrid environment, ensuring reliability, scalability, and secure ML operations across the production lifecycle in South Africa.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field.
• 3+ years of experience in software engineering, DevOps, or MLOps.
• Proficiency with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
• Experience with ML frameworks (TensorFlow, PyTorch) and MLOps tools (MLflow, Kubeflow).
• Strong understanding of automation and infrastructure as code (IaC).
• Excellent problem-solving and collaboration skills.

Responsibilities

• Design, implement, and manage CI/CD pipelines for machine learning models.
• Develop and maintain infrastructure for model training, deployment, and monitoring.
• Implement strategies for model versioning, experimentation tracking, and reproducibility.
• Collaborate with data scientists and software engineers to operationalize ML models.
• Monitor model performance in production and troubleshoot issues.
• Ensure the scalability, security, and reliability of the MLOps platform.

Skills

CI/CD

Cloud platforms

IaC

Collaboration

Problem-solving

Automation

Education

Bachelor's degree in Computer Science/Engineering

Tools

Docker

Kubernetes

MLflow

Kubeflow

Job description

About the Role

Our client is seeking a skilled Machine Learning Operations (MLOps) Engineer to join their team in Benoni . You will be instrumental in building and maintaining the infrastructure and workflows required to deploy, monitor, and manage machine learning models in production. This role bridges the gap between data science and operations, ensuring the reliability, scalability, and efficiency of our ML systems. You will work with cutting-edge MLOps tools and practices to streamline the ML lifecycle in a hybrid work setting.

Key Responsibilities

• Design, implement, and manage CI/CD pipelines for machine learning models.
• Develop and maintain infrastructure for model training, deployment, and monitoring.
• Implement strategies for model versioning , experimentation tracking, and reproducibility.
• Collaborate with data scientists and software engineers to operationalize ML models.
• Monitor model performance in production and troubleshoot issues.
• Ensure the scalability, security, and reliability of the MLOps platform.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field.
• 3+ years of experience in software engineering, DevOps, or MLOps.
• Proficiency with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
• Experience with ML frameworks (e.g., TensorFlow, PyTorch) and MLOps tools (e.g., MLflow, Kubeflow).
• Strong understanding of system automation and infrastructure as code (IaC).
• Excellent problem-solving and collaboration skills.

Benefits

• Competitive salary and comprehensive benefits.
• Hybrid work model offering flexibility.
• Access to advanced MLOps technologies and training.
• Opportunities for career growth in a high-demand field.
• A dynamic and innovative work environment in Benoni .