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...