Senior AI Infrastructure Engineer | MLOps & Kubernetes

EITACIES Inc.; San Francisco (CA); On-site; USD 120,000 - 150,000; Full time

Benefits offered by this job

401(k)

Job summary

EITACIES Inc. is looking for an experienced AI Infrastructure Engineer in San Francisco to support large-scale AI and machine learning platforms in cloud-native environments. The role involves designing and deploying scalable AI/ML infrastructure, managing AWS EKS Kubernetes environments, and troubleshooting complex production issues.

The ideal candidate will have over 10 years of Linux and Python experience, along with significant AWS and Kubernetes familiarity. This position is fully onsite in the San Francisco Bay Area, ensuring robust operational support.

Qualifications

• 10+ years of Linux systems administration and engineering experience.
• 10+ years of Python development and automation experience.
• 5+ years of Kubernetes administration and operations.
• 5+ years of AWS cloud experience, including AWS EKS.
• 5+ years of infrastructure automation using Ansible.

Responsibilities

• Design, deploy, and support scalable AI/ML infrastructure platforms.
• Manage Kubernetes environments running in AWS EKS.
• Build and maintain infrastructure automation using Python and Ansible.
• Support MLOps workflows including model deployment, monitoring, and operationalization.
• Troubleshoot complex Linux-based production environments.

Skills

Linux systems administration

Python development

Kubernetes operations

AWS cloud

Infrastructure automation using Ansible

Troubleshooting skills

Performance optimization skills

Job description

EITACIES Inc. is looking for an experienced AI Infrastructure Engineer in San Francisco to support large-scale AI and machine learning platforms in cloud-native environments. The role involves designing and deploying scalable AI/ML infrastructure, managing AWS EKS Kubernetes environments, and troubleshooting complex production issues.

The ideal candidate will have over 10 years of Linux and Python experience, along with significant AWS and Kubernetes familiarity. This position is fully onsite in the San Francisco Bay Area, ensuring robust operational support.