Data science or MLOps Platform Engineer

Role: Data science,MLOps Platform Engineer (SageMaker)
Location:  Plano, TX
Contract: 12 months will be extented only on w2

Required Skills: 
- 10-15 years of software engineering experience focused on cloud infrastructure or ML platform operations
- 5+ years hands-on with AWS, including deep expertise in Amazon SageMaker (Studio, Pipelines, Model Registry, Endpoints, Feature Store)
- 3+ years building and operating production MLOps pipelines — training, versioning, deployment, monitoring, rollback
- Experience with SageMaker Unified Studio or Studio Classic — domain/project setup, blueprints, multi-tenant configuration
- Infrastructure-as-Code with Terraform, CDK, or CloudFormation
- IAM design for ML platforms — execution roles, service roles, cross-account access, Lake Formation, SSO/SAML
- MLflow or equivalent experiment tracking
- SageMaker Pipelines or similar workflow orchestration (Airflow, Step Functions)
- Model serving — real-time endpoints, batch transform, auto-scaling, endpoint monitoring
- Snowflake as a data source for ML pipelines
- Kubernetes (EKS) and container orchestration
- Networking and security — VPC, security groups, private endpoints, cross-account connectivity