Machine Learning Operations (MLOps) Engineer

Placements24; Vereeniging; Hybrid; ZAR 720,000 - 900,000; Full time

Job summary

Placements24 is seeking a highly motivated Machine Learning Operations (MLOps) Engineer to join its technology team. The role is primarily remote with potential Vereeniging site engagement, focusing on operationalizing AI, building scalable ML infrastructure and CI/CD pipelines.

You will collaborate with data scientists and software engineers to automate training, testing, deployment and monitoring of ML models, applying IaC and best practices throughout the ML lifecycle.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field.
• Proven MLOps/DevOps experience with automation and infrastructure management.
• Proficiency with cloud platforms (AWS, Azure, or GCP) and containerization technologies (Docker, Kubernetes).
• Experience with scripting languages such as Python and familiarity with ML frameworks.
• Strong understanding of software development best practices and CI/CD principles applied to ML lifecycles.

Responsibilities

• Design, build, and maintain CI/CD pipelines for machine learning models.
• Implement infrastructure as code (IaC) for ML environments using tools like Terraform or Ansible.
• Develop and manage systems for model monitoring, versioning, and performance tracking.
• Collaborate with data scientists and software engineers to ensure smooth deployment and operation of ML models.
• Automate ML workflows, from data preparation to model retraining and deployment in Vereeniging.

Skills

MLOps

DevOps

CI/CD

Python

Cloud knowledge

Automation

Education

Bachelor's degree in Computer Science/Engineering

Tools

AWS

Azure

GCP

Docker

Kubernetes

Terraform

Ansible

Python

Job description

About the Role

Our client is seeking a highly motivated Machine Learning Operations (MLOps) Engineer to join their dynamic technology team, operating primarily remotely but with potential for Vereeniging site engagement. This role is essential for bridging the gap between machine learning model development and production deployment, ensuring seamless, scalable, and reliable ML systems. You will be responsible for building and managing the infrastructure, pipelines, and tools required to automate the training, testing, deployment, and monitoring of machine learning models. This is a fantastic opportunity for an engineer passionate about operationalizing AI and contributing to the efficiency and effectiveness of the company's cutting-edge AI and Emerging Technologies initiatives.

Key Responsibilities

• Design, build, and maintain CI/CD pipelines for machine learning models.
• Implement infrastructure as code (IaC) for ML environments using tools like Terraform or Ansible.
• Develop and manage systems for model monitoring, versioning, and performance tracking.
• Collaborate with data scientists and software engineers to ensure smooth deployment and operation of ML models.
• Automate ML workflows, from data preparation to model retraining and deployment in Vereeniging .

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field.
• Proven experience in MLOps, DevOps, or a similar role involving automation and infrastructure management.
• Proficiency with cloud platforms (AWS, Azure, or GCP) and containerization technologies (Docker, Kubernetes).
• Experience with scripting languages such as Python and familiarity with ML frameworks.
• Strong understanding of software development best practices and CI/CD principles applied to ML lifecycles.

Benefits

• Competitive salary and comprehensive benefits package.
• Flexible working arrangements, including a strong emphasis on remote work.
• Access to cutting-edge technologies and professional development opportunities.
• A collaborative team culture that encourages innovation and continuous improvement.
• The chance to work on impactful projects in the rapidly evolving field of AI and Machine Learning .