MLOps & DevOps Engineer — AI Infra & Cloud CI/CD

Openkrill; United States; Hybrid; USD 130,000 - 170,000; Full time

Job summary

CreatorIQ is seeking a DevOps/ML Ops Engineer to support cloud and ML/AI infrastructure, automate deployments, and maintain CI/CD pipelines. This role emphasizes secure, scalable, and automated workflows across product and data science teams.

We value collaboration across time zones in a flexible, hybrid work model that combines in-person and remote work to boost innovation and operational excellence. Strong emphasis on IaC, monitoring, security, and reliability.

Qualifications

• 3+ years in DevOps, Cloud Engineering, SRE or similar.
• 2+ years supporting production ML/AI infrastructure.
• 2+ years with Databricks and/or AWS SageMaker.
• 2+ years AWS services (EC2, S3, RDS, Lambda, IAM, VPC).
• 2+ years with Kubernetes/EKS.
• Strong CI/CD experience with GitLab CI/CD or Jenkins.
• IaC experience with Terraform, Terragrunt, CloudFormation.
• Strong Linux administration and networking fundamentals.
• Scripting in Python or Bash for automation.

Responsibilities

• Maintain scalable, highly available, secure cloud infrastructure.
• Provision resources using IaC (Terraform, Terragrunt, CloudFormation).
• Implement cloud security best practices including IAM, encryption and vulnerability management.
• Support containerized environments and orchestration platforms.
• Apply DevSecOps practices across infra and deployment workflows.
• Participate in disaster recovery planning and testing.
• Maintain CI/CD pipelines and deployment automation for apps and ML models.
• Support AI/agentic infrastructure including MCP and integrations.
• Maintain monitoring and observability for infra and ML workloads.

Skills

DevOps

Cloud Engineering

SRE

CI/CD

Python scripting

Tools

Databricks

AWS SageMaker

AWS EC2

S3

RDS

Lambda

IAM

VPC

Kubernetes

EKS

GitLab CI/CD

Jenkins

Terraform

Terragrunt

CloudFormation

Job description

CreatorIQ is seeking a DevOps/ML Ops Engineer to support cloud and ML/AI infrastructure, automate deployments, and maintain CI/CD pipelines. This role emphasizes secure, scalable, and automated workflows across product and data science teams.

We value collaboration across time zones in a flexible, hybrid work model that combines in-person and remote work to boost innovation and operational excellence. Strong emphasis on IaC, monitoring, security, and reliability.