ML DevOps Engineer

The ML DevOps Engineer will focus on building and maintaining the infrastructure and pipelines necessary for seamless ML model deployment and monitoring.

Task Description

• Design and implement automated infrastructure setups using tools like 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 the existing infrastructure.

• Create and manage environments (Development, Testing, Staging and Production).

• Implement monitoring and logging solutions to track performance, data drift, and versioning.

• Set up and manage containerisation using Docker for ML model deployment.

• Automate MLOps processes to improve efficiency and reliability.

• Collaborate with the ML Engineer to ensure smooth integration of models into production environments.