Vacancy 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<...
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<...
Ready to Apply?
अभी आवेदन करें
Submit your application for AWS SageMaker Engineer at Persistent Systems
Apply for this Position