Description

You will build and maintain the infrastructure and pipelines required for seamless ML model deployment and monitoring.

This role is on-site.

Responsibilities

• Design and implement automated infrastructure setups using Terraform, CloudFormation, or Kubernetes.
• Build and maintain CI/CD pipelines that incorporate model training, validation, and deployment.
• Integrate data pipelines, model training, and inference processes with existing infrastructure.
• Create and manage environments including Development, Testing, Staging, and Production.
• Implement monitoring and logging solutions to track performance, data drift, and versioning.

Required Skills

• 5+ years of experience in DevOps or MLOps engineering.
• Strong proficiency with containerization tools, specifically Docker.
• Experience designing automated infrastructure using Terraform, CloudFormation, or Kubernetes.
• Ability to build and maintain CI/CD pipelines for ML workflows.
• Experience integrating data pipelines and inference processes into production environments.
• Expertise in implementing monitoring and logging solutions for model performance and data drift.
• Bachelor's degree in any discipline (Any Graduate).

Key Skills

Education

Any Graduate