Description

You will design and maintain CI/CD pipelines for AI/ML applications, deploying workloads on AWS, Azure, or GCP. You automate infrastructure provisioning and manage Kubernetes and Docker environments while implementing MLOps solutions for model lifecycle management.

This role is on-site.

Responsibilities

• Design and maintain CI/CD pipelines for AI/ML applications.
• Deploy and manage AI/ML workloads on AWS, Azure, or GCP.
• Automate infrastructure provisioning using Terraform, CloudFormation, or Bicep.
• Manage Kubernetes, Docker, and cloud-native services.
• Implement MLOps solutions for model training, deployment, monitoring, and retraining.

Required Skills

• 5+ years of DevOps and Cloud Engineering experience with AWS, Azure, or GCP.
• Proficiency in Kubernetes, Docker, and Helm.
• Experience with Terraform, Git, and CI/CD tools like Jenkins, GitHub Actions, or Azure DevOps.
• Strong Python and Shell Scripting skills.
• Familiarity with MLOps tools such as MLflow, Kubeflow, Airflow, SageMaker, or Azure ML.
• Experience with Generative AI, LLMs, and AI model deployment.

Preferred Skills

• Implementing DevSecOps best practices.
• Monitoring application and infrastructure performance using observability tools.

Key Skills

Education

Bachelor's or Master's degrees