Source description
About the role
AWS Sage Maker
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Job Info
- Job Identification15902
- Posting Date06/30/2026, 06:27 AM
- Job RoleApplication Development-Applications Development Engineering
- Experience (In Years)12-15
- Job LocationIndia
Job Description
Requirements
- 10+ years of experience with at least 7+ years of AWS cloud transformation & DevOps
- Experience in designing, deploying, and managing end-to-end machine learning (ML) lifecycles using Amazon SageMaker
- Designing and maintaining CI/CD pipelines for ML, containerizing models with Docker, and setting up SageMaker endpoints
- Monitoring model health, managing infrastructure, and ensuring data governance
- A strong understanding of evolving DevOps, SRE, Observability ecosystem in the context of hybrid cloud
- Defining persona-based roles with SageMaker Role Manager, creating SageMaker Unified Studio domains/user profiles, and managing VPC configurations.
- 5 + years AWS Architecture experience is highly desirable
- AWS Solution Architect certification is highly desirable
Responsibilities
Requirements
- 10+ years of experience with at least 7+ years of AWS cloud transformation & DevOps
- Experience in designing, deploying, and managing end-to-end machine learning (ML) lifecycles using Amazon SageMaker
- Designing and maintaining CI/CD pipelines for ML, containerizing models with Docker, and setting up SageMaker endpoints
- Monitoring model health, managing infrastructure, and ensuring data governance
- A strong understanding of evolving DevOps, SRE, Observability ecosystem in the context of hybrid cloud
- Defining persona-based roles with SageMaker Role Manager, creating SageMaker Unified Studio domains/user profiles, and managing VPC configurations.
- 5 + years AWS Architecture experience is highly desirable
- AWS Solution Architect certification is highly desirable
Qualifications
Requirements
- 10+ years of experience with at least 7+ years of AWS cloud transformation & DevOps
- Experience in designing, deploying, and managing end-to-end machine learning (ML) lifecycles using Amazon SageMaker
- Designing and maintaining CI/CD pipelines for ML, containerizing models with Docker, and setting up SageMaker endpoints
- Monitoring model health, managing infrastructure, and ensuring data governance
- A strong understanding of evolving DevOps, SRE, Observability ecosystem in the context of hybrid cloud
- Defining persona-based roles with SageMaker Role Manager, creating SageMaker Unified Studio domains/user profiles, and managing VPC configurations.
- 5 + years AWS Architecture experience is highly desirable
- AWS Solution Architect certification is highly desirable
Required Skills
- Adapting To Change
- Attention To Consistency
- Cloud Platforms
- Data Pipeline Architecture
- Interpersonal Dynamics with Coworkers
- Python Programming Language
- Results Orientation
- SQL Programming Language
- Shell Scripting
- Time Management Skills
- Working under Pressure
- Writing Communication Skills
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