Description

You will manage the end-to-end lifecycle of machine learning models within the SageMaker ecosystem.

Responsibilities

• Improve model pipelines between SageMaker Model Registry and SageMaker Endpoints for QA and PROD deployments.
• Implement model lineage using model cards in SageMaker Model Registry to track data versions and Bitbucket tags.
• Deploy multi-model SageMaker Model Endpoints and integrate them with Azure AD (SIGA).
• Develop and implement model monitoring solutions for models running in QA and PROD environments.
• Collaborate with architects and DevOps to design model deployment and monitoring workflows following the 2025 DEEP migration.

Required Skills

• 5+ years of experience in machine learning engineering or related roles.
• Hands-on experience with Amazon SageMaker.
• Proficiency with SageMaker Model Registry.
• Experience managing model deployments via SageMaker Endpoints.
• Knowledge of Azure AD integration.
• Understanding of DevOps practices.
• Experience with Bitbucket for version control.

Preferred Skills

• Any Graduate degree.

Key Skills

Education

Any Graduate