MLOps Platform Engineer

W2 contract (only USC/GC)

• 
  10-15 years of software engineering experience focused on cloud infrastructure or ML platform operation
• s5+ 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, rollbac
• kExperience with SageMaker Unified Studio or Studio Classic — domain/project setup, blueprints, multi-tenant configuratio
• nInfrastructure-as-Code with Terraform, CDK, or CloudFormatio
• nIAM design for ML platforms — execution roles, service roles, cross-account access, Lake Formation, SSO/SAM
• LMLflow or equivalent experiment trackin
• gSageMaker Pipelines or similar workflow orchestration (Airflow, Step Functions
• )Model serving — real-time endpoints, batch transform, auto-scaling, endpoint monitorin
• gSnowflake as a data source for ML pipeline
• sKubernetes (EKS) and container orchestratio
• nNetworking and security — VPC, security groups, private endpoints, cross-account connectivit