Summary
An organization is looking for a DevOps engineer to design and maintain cloud-native infrastructure, improve automation, support machine learning platforms, and build reliable deployment pipelines.
Highlights
Hands-on engineering role focused on modern cloud infrastructure, automation, scalability, and advanced platform development.
Description
Role: DevOps Engineer
Location: Columbus, OH (Hybrid/Onsite)
Job Type: Contract to Hire
📌 About the Rol
eLooking for a highly skilled DevOps Engineer with a strong background in cloud-native technologies, Kubernetes, and GitOps practices.
In this role, you will design, build, and maintain scalable infrastructure while also contributing to the development of modern ML platforms and automation systems
.This is a hands-on engineering role requiring strong problem-solving skills and the ability to work beyond conventional approaches to deliver innovative, reliable solutions
.
✅ Key Responsibiliti
esDesign and implement cloud-native infrastructure using AWS (EKS, ECS, ECR)Build and manage Kubernetes-based platforms using Docker and HelmDevelop and maintain GitOps workflows for continuous deliveryWrite Python-based automation tools to improve operational efficiencyCreate and maintain infrastructure using Terraform (advanced level)Build scalable ML infrastructure for model training, deployment, and monitoringDevelop and optimize CI/CD pipelines (Jenkins, GitLab CI)Implement monitoring and observability using Prometheus and GrafanaIdentify and automate solutions for recurring production issuesConduct technical evaluations of tools, vendors, and architecturesEnsure systems are secure, scalable, and production-rea
dy
🔧 Required Skills & Experie
nceStrong experience with Kubernetes, Docker, and container orchestrationHands-on expertise in AWS (EKS, ECS, ECR)Deep understanding of GitOps practicesAdvanced proficiency with TerraformStrong programming skills in Python (automation, scripting, tooling)Experience with CI/CD pipelines (Jenkins, GitLab CI, GitHub)Solid understanding of cloud-native architecturesBachelor’s degree in Computer Science, Engineering, or related field (requir
ed)
⭐ Nice to
HaveExperience with MLOps / ML platform engineeringFamiliarity with Kubeflow or similar frameworksKnowledge of AI/ML development workflowsExperience with multi-cloud environmentsAdvanced monitoring and observability expertiseUnderstanding of modern deployment strategies (canary, blue-green, e
tc.)
