ML Ops Engineer

Smart IT Frame LLC; Atlanta (GA); On-site; USD 120,000 - 180,000; Full time

Job summary

Smart IT Frame LLC seeks a seasoned cloud engineering professional to lead platform, DevOps, and infrastructure initiatives in Atlanta. The role emphasizes hands-on AWS, SageMaker, Terraform, and CI/CD, with a focus on secure cloud design, automation, and cost optimization.

Collaboration across teams and strong documentation are essential. The ideal candidate will design reusable, scalable solutions, implement secure access controls, and continuously improve observability and resiliency of cloud

Qualifications

• Experience in cloud engineering, platform engineering, DevOps, infrastructure engineering, or related technology roles.
• Strong hands-on experience with AWS services and cloud-native engineering.
• Experience with AWS SageMaker or comparable enterprise Data Science / ML platforms.
• Strong automation and scripting experience using Python, shell, or similar technologies.
• Experience with Terraform, infrastructure-as-code, and CI/CD engineering.
• Strong troubleshooting, systems analysis, and root-cause-analysis capabilities.
• Experience engineering secure cloud environments, including identity/access controls and vulnerability remediation.
• Experience with monitoring, observability, resiliency, and platform-performance engineering.
• Experience with cloud cost optimization and resource-efficiency improvements.
• Ability to design reusable solutions that reduce manual operational processes.
• Strong communication, technical documentation, and cross-team collaboration skills.

Skills

Cloud engineering

Platform engineering

DevOps

Infrastructure engineering

AWS

SageMaker

Python scripting

Shell scripting

Terraform

IaC

CI/CD

Troubleshooting

IAM

Vulnerability remediation

Monitoring

Observability

Resiliency

Cost optimization

Automation design

Communication

Documentation

Collaboration

Job description

• Experience in cloud engineering, platform engineering, DevOps, infrastructure engineering, or related technology roles.
• Strong hands-on experience with AWS services and cloud-native engineering.
• Experience with AWS SageMaker or comparable enterprise Data Science / ML platforms.
• Strong automation and scripting experience using Python, shell, or similar technologies.
• Experience with Terraform, infrastructure-as-code, and CI/CD engineering.
• Strong troubleshooting, systems analysis, and root-cause-analysis capabilities.
• Experience engineering secure cloud environments, including identity/access controls and vulnerability remediation.
• Experience with monitoring, observability, resiliency, and platform-performance engineering.
• Experience with cloud cost optimization and resource-efficiency improvements.
• Ability to design reusable solutions that reduce manual operational processes.
• Strong communication, technical documentation, and cross-team collaboration skills.