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# Mlops DevOps

- **Company:** Staffxpert Llc
- **Location:** Atlanta, GA, United States
- **Experience:** Expert
- **Salary:** $105,000.0 - $160,000.0
- **Contract:** Temporary to permanent
- **Skills:** Amazon Web Services, Audit Trail, Cloud Computing, Cloud Computing Security, Information Engineering, DevOps, Monitoring of Systems, Identity and Access Management, Python (Programming Language), Machine Learning, Amazon Simple Notification Service (SNS), Management of Software Versions, Snowflake, Amazon Virtual Private Cloud (VPC), Containerization, Pyspark, Gitlab-ci, Performance Monitor, Machine Learning Operations, Cloudwatch, Terraform, Data Pipelines, Docker
- **Published:** July 20, 2026
- **Apply:** https://www.careerjet.com/jobad/usd8c25684c3d97b6e11440ac62fd0d93e

## About the Role

* AWS SageMaker & SageMaker Domains
 * MLOps / ML Pipeline Development
 * GitLab CI/CD
 * Terraform / Infrastructure as Code
 * Docker & Amazon ECR
 * AWS VPC & IAM
 * Python & PySpark
 * Snowflake
 * SageMaker Model Monitoring (Drift & Performance)
 * AWS SNS / CloudWatch
 * Model Deployment & Governance
 * AWS Cloud Security & Compliance

Experience with AWS VPC, IAM, SNS, PySpark, Snowflake, and SageMaker Model Monitoring is required. The ideal candidate should also have experience with model drift/performance monitoring, cloud security, governance, auditability, and compliance, preferably within the banking or financial services industry.
Key Skills: AWS SageMaker | SageMaker Domains | MLOps | GitLab CI/CD | Terraform | Docker | ECR | VPC | IAM | SNS | PySpark | Snowflake | Model Monitoring | Python | AWS Cloud Security.

## Description

* Build and manage end-to-end MLOps pipelines using AWS SageMaker and SageMaker Domains.
 * Develop GitLab CI/CD pipelines for automated model build, testing, and deployment.
 * Automate AWS infrastructure using Terraform / IaC.
 * Containerize workloads using Docker and manage images through Amazon ECR.
 * Design secure AWS environments using VPC, IAM, Security Groups, and SNS.
 * Develop data pipelines using PySpark and integrate with Snowflake.
 * Implement SageMaker model monitoring for drift, performance, data quality, and alerts.
 * Support model deployment, versioning, rollback, monitoring, and troubleshooting.
 * Ensure security, governance, compliance, and auditability of MLOps workflows in a banking environment.
 * Collaborate with Data Science, ML Engineering, Data Engineering, Cloud, and Security teams.


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