AWS Architect - ML & SageMaker

Remote • Posted 19 days ago • Updated 19 days ago
Contract Independent
Contract W2
No Travel Required
Remote
Depends on Experience
Fitment

Dice Job Match Score™

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Job Details

Skills

  • AWS Architect
  • ML
  • SageMaker
  • Amazon S3
  • AWS Lambda
  • Amazon EKS
  • Container Orchestration
  • AWS CodePipeline
  • Python
  • TensorFlow
  • PyTorch
  • Scikit-learn
  • Docker
  • Infrastructure as Code

Summary

Job Title: AWS Architect – ML & SageMaker   

Location: FULLY Remote

Position type: Long term Contract

Rate: DOE

 

Description:-

We are seeking an experienced AWS Architect with strong hands-on expertise in Amazon SageMaker to design and implement scalable, secure, and production-grade ML platforms on AWS.

The role will own architecture decisions across data ingestion, model training, deployment, MLOps, and governance.

 

Key Responsibilities:

Architect end-to-end ML platforms using SageMaker and core AWS services

Design scalable training and inference pipelines (real-time & batch)

Implement CI/CD for ML workflows and model versioning

Establish MLOps best practices (monitoring, drift detection, rollback strategies)

Define secure, multi-account AWS architecture and networking patterns

Optimize cost, performance, and reliability of ML workloads

Guide engineering teams on cloud-native and microservices-based ML design

 

Required Skills & Experience:

8+ years in cloud architecture; 3+ years hands-on with SageMaker

 

Strong experience with:

Amazon S3

AWS Lambda

Amazon EKS or container orchestration

AWS CodePipeline

Proficiency in Python and ML frameworks (TensorFlow / PyTorch / scikit-learn)

Experience with Docker and Infrastructure as Code (Terraform/CloudFormation)

Strong understanding of distributed systems and event-driven architectures

 

Good to Have:

Experience with GenAI/ LLM deployment

Feature store and model registry implementation

 

Skills Matrix:-

Total work experience in IT Industry: Years

Total work experience in USA: Years

AWS Architect: Years

ML: Years

SageMaker: Years

Amazon S3: Years

AWS Lambda: Years

Amazon EKS or Container Orchestration: Years

AWS CodePipeline: Years

Python and ML frameworks (TensorFlow / PyTorch / scikit-learn): Years

Experience with Docker and Infrastructure as Code (Terraform/CloudFormation): Years

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 10412228
  • Position Id: 8886650
  • Posted 19 days ago
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