MLOps Platform Engineer (SageMaker)

Duration: 12 months with extension

Location: Onsite at Plano, TX 75024

Requirements:

Qualifications/ What you bring (Must Haves) – Highlight Top 3-5 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

Added bonus if you have (Preferred):    

- SageMaker Unified Studio domain provisioning, custom blueprints, project standardization

- SageMaker Feature Store for online/offline feature management

- SageMaker Model Monitor — data quality checks, bias detection, drift detection

- AWS Machine Learning Specialty certification