MLOps Platform Engineer (SageMaker)

Job Title: MLOps Platform Engineer (SageMaker)

Job Type: Contract

Duration: 12 months contract with extension

Location: Plano, TX 75024

Onsite role

What we’re looking for

Enterprise Platforms team is looking for a Senior ML Platform Engineer to design, build, and operationalize an enterprise ML platform on AWS SageMaker Unified Studio. You will migrate the organization from a fragmented ML toolchain to a unified, governed platform on AWS Landing Zone 2, covering the full ML lifecycle from data discovery through model deployment and monitoring.

What you’ll be doing

• Set up SageMaker Unified Studio platform — domain configuration, project provisioning, persona-based roles, and multi-environment (Dev, Prod-UAT, Prod) promotion workflows

• Build MLOps pipelines using SageMaker Pipelines — data extraction from Snowflake, preprocessing, training, evaluation, and model registration

• Manage SageMaker Model Registry — cross-account model promotion, versioning, immutability, and lineage tracking

• Configure MLflow experiment tracking — auto-logging of parameters, metrics, and artifacts

• Set up identity and access management — Okta SSO, SailPoint entitlements, persona-based execution roles, service roles for pipelines

• Build model serving — real-time SageMaker endpoints and batch prediction workflows

• Set up model monitoring — data drift, model drift, performance degradation detection

• Configure data catalog — searchable datasets, access-level visibility, access-request workflows, lineage

• Own platform operations — observability (CloudWatch, Datadog), logging, custom images, instance availability

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 connectiv ity

• 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

• Pay rate: 102-102 USD per Hour Job type: Contract Division: eTeam Inc (US) Category: eTeam United States Reference: 26-53721