Found Description
About Position:
We are seeking an experienced AWS SageMaker Engineer to design and build scalable MLOps platforms and machine learning pipelines on AWS. The role focuses on enabling end-to-end ML lifecycle management including model development, deployment, monitoring, and automation. The ideal candidate will have strong expertise in SageMaker, cloud-native architecture, and DevOps practices, along with the ability to collaborate with data science teams to productionize ML use cases efficiently.
Role :
AWS SageMaker Engineer
Location: All Persistent Location
Experience: 8-12 years
Job Type: Full Time Employment
What You'll Do:
Design and implement end-to-end MLOps pipelines on Amazon SageMaker for training, validation, deployment, and monitoring
Build DevOps automation to provision and manage ML infrastructure across environments
Develop Python-based tools and frameworks to standardize ML workflows and platform operations
I...
We are seeking an experienced AWS SageMaker Engineer to design and build scalable MLOps platforms and machine learning pipelines on AWS. The role focuses on enabling end-to-end ML lifecycle management including model development, deployment, monitoring, and automation. The ideal candidate will have strong expertise in SageMaker, cloud-native architecture, and DevOps practices, along with the ability to collaborate with data science teams to productionize ML use cases efficiently.
Role :
AWS SageMaker Engineer
Location: All Persistent Location
Experience: 8-12 years
Job Type: Full Time Employment
What You'll Do:
Design and implement end-to-end MLOps pipelines on Amazon SageMaker for training, validation, deployment, and monitoring
Build DevOps automation to provision and manage ML infrastructure across environments
Develop Python-based tools and frameworks to standardize ML workflows and platform operations
I...