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. | - 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.
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