AI/ML Infrastructure Engineer

Placements24; LegKraal Gate; Hybrid; ZAR 900,000 - 1,500,000; Full time

Benefits offered by this job

Competitive salary

Performance-based bonuses

Health, dental, and vision insurance

Professional development opportunities

Access to cutting-edge infrastructure

Job summary

Placements24 seeks an AI/ML Infrastructure Engineer to build scalable cloud-based platforms powering AI initiatives in Mahikeng. You will design, implement, and manage robust ML infra, focusing on reliability, performance, and cost efficiency to support data scientists and ML engineers.

You will collaborate closely with AI teams, implement MLOps pipelines, and ensure security and observability of the infrastructure across AWS/Azure/GCP environments.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or related field.
• 3+ years of experience in DevOps, SRE, or infrastructure engineering with AI/ML focus.
• Proficiency with cloud platforms (AWS, Azure, GCP).
• Experience with Docker and Kubernetes.
• Strong CI/CD knowledge (Jenkins, GitLab CI).
• IaC experience with Terraform and Ansible.

Responsibilities

• Design, build, and maintain scalable AI/ML infra on cloud platforms (AWS/Azure/GCP).
• Implement and manage MLOps pipelines for CI/CD, testing, deployment, and monitoring.
• Optimize resources for cost-effectiveness and performance for ML workloads.
• Develop and manage Docker and Kubernetes ecosystems for ML apps.
• Ensure security, stability, and observability of AI/ML infrastructure.
• Collaborate with data scientists/ML engineers to support infra needs.

Skills

DevOps

SRE

Cloud proficiency

CI/CD

Education

Bachelor's degree in Computer Science or related field

Tools

Docker

Kubernetes

Terraform

Ansible

Jenkins

GitLab CI

Job description

About the Role

Our client is looking for a skilled AI/ML Infrastructure Engineer to build and maintain the scalable infrastructure that powers their AI & Emerging Technologies initiatives in Mahikeng . You will be responsible for designing, implementing, and managing robust cloud-based platforms, ensuring high availability, performance, and efficiency for machine learning operations (MLOps). This role requires a strong blend of DevOps principles and a deep understanding of AI/ML workflows. You will collaborate closely with data scientists and ML engineers to provide the essential tools and environment needed for cutting-edge AI development and deployment, fostering a culture of reliability and innovation.

Key Responsibilities

• Design, build, and maintain scalable, reliable, and performant infrastructure for AI/ML workloads on cloud platforms (e.g., AWS, Azure, GCP).


• Implement and manage MLOps pipelines for CI/CD, automated testing, model deployment, and monitoring.


• Optimize infrastructure resources for cost-effectiveness and performance, particularly for deep learning training and inference.


• Develop and manage containerization (Docker) and orchestration (Kubernetes) solutions for ML applications.


• Ensure security, stability, and observability of the AI/ML infrastructure.


• Collaborate with data scientists and ML engineers to understand their infrastructure needs and provide support.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related technical field.


• 3+ years of experience in DevOps, Site Reliability Engineering (SRE), or infrastructure engineering, with a focus on AI/ML.


• Proficiency with cloud platforms (AWS, Azure, GCP) and their relevant services for ML.


• Experience with containerization (Docker) and orchestration (Kubernetes).


• Strong understanding of CI/CD principles and tools (e.g., Jenkins, GitLab CI).


• Knowledge of infrastructure-as-code tools (e.g., Terraform, Ansible).

Benefits

• Competitive salary and performance-based bonuses.


• Comprehensive health, dental, and vision insurance.


• Opportunities for professional development and certifications in cloud and MLOps.


• Access to cutting-edge infrastructure and tools for AI development.


• A dynamic team environment focused on enabling AI innovation.