AI/ML Infrastructure Engineer

Placements24; East London; Hybrid; ZAR 900,000 - 1,300,000; Full time

Benefits offered by this job

Flexible remote work options

Professional development budget

Access to cutting-edge hardware and AI

Job summary

Placements24 in South Africa seeks an experienced AI/ML Infrastructure Engineer to design, deploy, and manage scalable AI infrastructure supporting large-scale model training and data pipelines across cloud and on-premise clusters.

You will implement MLOps workflows, optimize pipelines, develop automation tools, and collaborate with data scientists to ensure reliability, security, and performance of the AI environment.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related technical field.
• 4+ years of experience in infrastructure engineering, with a focus on AI/ML environments.
• Proficiency with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
• Experience with infrastructure as code tools (e.g., Terraform, Ansible).
• Solid understanding of distributed systems, networking, and storage solutions.
• Familiarity with deep learning frameworks and MLOps best practices is essential.

Responsibilities

• Design, build, and maintain scalable and robust infrastructure for AI/ML workloads.
• Manage cloud-based ML platforms and on-premises computing clusters.
• Implement and optimize MLOps pipelines for model training, deployment, and monitoring.
• Develop automation tools and scripts for infrastructure provisioning and management.
• Ensure the security, performance, and reliability of the AI infrastructure.
• Collaborate with data scientists and ML engineers to understand their infrastructure needs.

Skills

Distributed systems

Cloud computing

MLOps

Collaboration with data scientists

Education

Bachelor's degree in Computer Science or related field

Tools

Docker

Kubernetes

Terraform

Ansible

Job description

About the Role

Our client is seeking an experienced AI/ML Infrastructure Engineer to build and maintain the high-performance computing environment necessary for their advanced artificial intelligence research and development in Queenstown. You will be responsible for designing, deploying, and managing the infrastructure that supports large-scale machine learning model training, data pipelines, and MLOps workflows. This critical role requires a strong background in distributed systems, cloud computing, and deep learning frameworks. You will ensure the reliability, scalability, and efficiency of our AI infrastructure, enabling our research teams to push the boundaries of AI innovation.

Key Responsibilities

• Design, build, and maintain scalable and robust infrastructure for AI/ML workloads.
• Manage cloud-based ML platforms and on-premises computing clusters.
• Implement and optimize MLOps pipelines for model training, deployment, and monitoring.
• Develop automation tools and scripts for infrastructure provisioning and management.
• Ensure the security, performance, and reliability of the AI infrastructure.
• Collaborate with data scientists and ML engineers to understand their infrastructure needs.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related technical field.
• 4+ years of experience in infrastructure engineering, with a focus on AI/ML environments.
• Proficiency with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
• Experience with infrastructure as code tools (e.g., Terraform, Ansible).
• Solid understanding of distributed systems, networking, and storage solutions.
• Familiarity with deep learning frameworks and MLOps best practices is essential.

Benefits

• Highly competitive salary and comprehensive benefits package.
• Flexible remote work options for eligible candidates.
• Generous budget for professional development, certifications, and conferences.
• Access to cutting-edge hardware and software for AI development.
• A collaborative and forward-thinking work culture dedicated to technological advancement.