Senior AI Infrastructure Engineer

Placements24; Cape Town; On-site; ZAR 1,200,000 - 1,800,000; Full time

Benefits offered by this job

Competitive salary

Professional development

Impactful projects

Collaborative team

Job summary

Placements24 in Kimberley is seeking a Senior AI Infrastructure Engineer to design and maintain scalable AI infrastructure, ensuring availability and security for advanced AI initiatives.

You will manage GPUs/TPUs, Kubernetes, Docker, and CI/CD pipelines for ML models, optimizing training and deployment while collaborating with researchers and engineers to meet infrastructure needs.

Qualifications

• 6+ years in infrastructure engineering, with AI/ML focus.
• Experience with AWS, Azure, or GCP and Kubernetes.
• Scripting in Python or Bash; Terraform/Ansible.
• Understanding of distributed systems, networking, storage for large AI workloads.

Responsibilities

• Design and manage scalable AI infrastructure.
• Oversee GPUs/TPUs and software stack (Kubernetes, Docker).
• Develop CI/CD pipelines for ML models and infrastructure.
• Monitor performance and optimize training and inference.
• Ensure data security, compliance, and disaster recovery.

Skills

Distributed systems

Cloud platforms

Kubernetes

Python

Bash

Terraform

Ansible

AI/ML infra

Security/compliance

Education

BS/MS in CS or related

Tools

Kubernetes

Docker

Terraform

Ansible

Job description

About the Role

Our client is seeking a highly experienced Senior AI Infrastructure Engineer to build and maintain the robust, scalable infrastructure that powers their advanced AI initiatives in Kimberley . This role is fundamental to ensuring the efficient development, training, and deployment of machine learning models. You will architect and manage the hardware and software systems that support our cutting-edge AI research and product development, ensuring high availability, performance, and security. The ideal candidate is deeply knowledgeable about distributed systems, cloud computing, and the unique demands of AI workloads.

Key Responsibilities

• Design, implement, and manage scalable, reliable, and secure infrastructure for AI and machine learning workloads .
• Oversee the deployment, configuration, and maintenance of hardware (e.g., GPUs, TPUs) and software (e.g., Kubernetes, Docker).
• Develop and maintain CI/CD pipelines for ML models and infrastructure, enabling rapid iteration and deployment.
• Monitor system performance, identify bottlenecks, and implement optimizations for training and inference.
• Collaborate with AI researchers and engineers to understand their infrastructure needs and provide solutions.
• Ensure data security, compliance, and disaster recovery protocols are in place for AI systems.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
• 6+ years of experience in infrastructure engineering, DevOps, or Site Reliability Engineering, with a focus on AI/ML environments .
• Strong experience with cloud platforms (AWS, Azure, GCP) and container orchestration (Kubernetes).
• Proficiency in scripting languages (e.g., Python, Bash) and infrastructure as code tools (e.g., Terraform, Ansible).
• Deep understanding of distributed systems, networking, and storage solutions relevant to large-scale AI computations.
• Experience with GPU management and optimization for deep learning training is highly desirable.

Benefits

• Exceptional salary and comprehensive benefits package.
• Opportunities for professional development and advanced training in AI infrastructure.
• Be a key contributor to the foundational technology driving AI innovation in Kimberley .
• Work with a talented team on challenging and impactful projects.
• A supportive and collaborative work environment focused on technological excellence.