Senior ML Platform Engineer - AWS SageMaker & MLOps

B12 Consulting; Plano (TX); On-site; USD 150,000 - 190,000; Full time

Job summary

B12 Consulting in Plano, TX is seeking a Senior ML Platform Engineer to design, build, and operate 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.

You’ll design and set up SageMaker Unified Studio, build MLOps pipelines, manage the Model Registry and lineage, implement IAM and

Qualifications

• 10-15 years of software engineering focused on cloud infrastructure or ML platform ops.
• 5+ years AWS with SageMaker expertise (Studio, Pipelines, Model Registry, Endpoints, Feature Store).
• 3+ years building and operating production MLOps pipelines (training, versioning, deployment, monitoring).
• Experience with SageMaker Unified Studio or Studio Classic (domain setup, blueprints, multi-tenant).
• Infrastructure-as-Code: Terraform, CDK, or CloudFormation.
• IAM design for ML platforms — execution roles, cross-account access, SSO/SAML.
• MLflow or equivalent experiment tracking, SageMaker Pipelines orchestration.
• Model serving — real-time endpoints, batch, auto-scaling, monitoring.
• Snowflake as a data source for ML pipelines, Kubernetes (EKS).
• Networking and security — VPC, private endpoints, cross-account connectivity.

Responsibilities

• Set up SageMaker Unified Studio platform — domain config, project provisioning, roles, multi-environment promotion workflows.
• Build MLOps pipelines with SageMaker Pipelines — data extraction from Snowflake, preprocessing, training, evaluation, model registration.
• Manage SageMaker Model Registry — cross-account promotion, versioning, lineage tracking, immutability.
• Configure MLflow experiment tracking — auto-logging of parameters, metrics, artifacts.
• Set up IAM/Okta SSO and service roles for pipelines and environments.
• Build model serving — real-time endpoints and batch prediction workflows.
• Configure data catalog — searchable datasets, lineage, access requests.
• Own platform operations — observability (CloudWatch, Datadog), logging, images, instance availability.

Skills

10-15 years software engineering

SageMaker (Studio, Pipelines, Model) 5

MLOps pipelines (training, deployment,

Unified Studio / Studio Classic

Terraform/CDK/CloudFormation

IAM design for ML platforms

MLflow experiment tracking

SageMaker Pipelines orchestration

Model serving endpoints

Snowflake as data source

Kubernetes (EKS)

Networking and security (VPC, SGs)

Tools

Terraform

CDK

CloudFormation

Snowflake

Kubernetes (EKS)

Airflow / Step Functions

Job description

B12 Consulting in Plano, TX is seeking a Senior ML Platform Engineer to design, build, and operate 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.

You’ll design and set up SageMaker Unified Studio, build MLOps pipelines, manage the Model Registry and lineage, implement IAM and