Description

Key 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.
• Monitor application and infrastructure performance using observability tools.
• Collaborate with Data Scientists, ML Engineers, and Development teams.
• Implement DevSecOps best practices and ensure platform reliability.

Required Skills

• DevOps & Cloud Engineering (AWS/Azure/GCP)
• Kubernetes, Docker, Helm
• Terraform, Git, CI/CD (Jenkins, GitHub Actions, Azure DevOps)
• Python and Shell Scripting
• MLOps tools (MLflow, Kubeflow, Airflow, SageMaker, Azure ML)
• Experience with Generative AI, LLMs, and AI model deployment

Key Skills

Education

Any Gradute