Key skills
Machine LearningMLMLOpsMLflowBISnowflakeAirflowAWSTerraformKubernetesEKSCloudFormationIAMCloudWatchSageMakerOktaSAMLSSODatadog
About this role
CALL US NOW for immediate consideration! Click Apply on Web or Apply Now to view our recruiter s contact info and reach out today, we d love to speak with you!
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** We will NOT accept 3rd Party (C2C) Contractors **
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JOB DETAILS:
Position:MLOps Platform Engineer (SageMaker)
JOB REF#:
Duration:12+ Months (On-going Contract)
Location:ONSITE - Plano, TX 75024
Pay Rate:OPEN/Market Rate (W2 ONLY)
This role is 100% ONSITE (Must be local or willing to relocate at your own expense)
HOURS: MON- FRI 8am - 5pm
Seeking to hire a MLOps Platform Engineer (Sagemaker) who is expert in Sagemaker and AWS (key skill sets). They will be design, build, and operationalize an enterprise ML platform on AWS SageMaker Unified Studio. You will migrate the organization from a fragmented ML tool chain to a unified, governed platform on AWS Landing Zone 2, covering the full ML lifecycle from data discovery through model deployment and monitoring. They will work with the Enterprise Analytical Data & Integration Team.
RESPONSIBILITIES INCLUDE:
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
REQUIRED SKILLS/EXPERIENCE:
** MLOps Platform Engineer (Sagemaker) with expertise in SageMaker and AWS (key skill sets).
MANDATORY SKILLS:
10+ years of Software Engineering experience focused on cloud infrastructure or ML platform operations.
5+ years hands-on experience with AWS, including deep expertise in Amazon SageMaker (Studio Classic 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)
MLflow or equivalent experiment tracking
SageMaker Pipelines or similar workflow orchestration (Airflow, Step Functions)
Unified Studio is preferred to have but Classic is must
Other skills:
Infrastructure-as-Code with Terraform, CDK, or CloudFormation
IAM design for ML platforms execution roles, service roles, cross-account access, Lake Formation, SSO/SAML
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
DESIRED SKILLS:
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
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Calance Consultant Benefits Offerings:
- EPO/PPO Medical Plans
- HMO/PPO Dental programs
- Vision - VSP (Vision Plan Summary)
- 401K Retirement vesting program (VOYA)
- Paid Bi-Weekly/Direct Deposit
- Flex Spending Plan
- Voluntary Life, AD&D, STD or LTD plans
===
** We will NOT accept 3rd Party (C2C) Contractors **
===
JOB DETAILS:
Position:MLOps Platform Engineer (SageMaker)
JOB REF#:
Duration:12+ Months (On-going Contract)
Location:ONSITE - Plano, TX 75024
Pay Rate:OPEN/Market Rate (W2 ONLY)
This role is 100% ONSITE (Must be local or willing to relocate at your own expense)
HOURS: MON- FRI 8am - 5pm
Seeking to hire a MLOps Platform Engineer (Sagemaker) who is expert in Sagemaker and AWS (key skill sets). They will be design, build, and operationalize an enterprise ML platform on AWS SageMaker Unified Studio. You will migrate the organization from a fragmented ML tool chain to a unified, governed platform on AWS Landing Zone 2, covering the full ML lifecycle from data discovery through model deployment and monitoring. They will work with the Enterprise Analytical Data & Integration Team.
RESPONSIBILITIES INCLUDE:
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
REQUIRED SKILLS/EXPERIENCE:
** MLOps Platform Engineer (Sagemaker) with expertise in SageMaker and AWS (key skill sets).
MANDATORY SKILLS:
10+ years of Software Engineering experience focused on cloud infrastructure or ML platform operations.
5+ years hands-on experience with AWS, including deep expertise in Amazon SageMaker (Studio Classic 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)
MLflow or equivalent experiment tracking
SageMaker Pipelines or similar workflow orchestration (Airflow, Step Functions)
Unified Studio is preferred to have but Classic is must
Other skills:
Infrastructure-as-Code with Terraform, CDK, or CloudFormation
IAM design for ML platforms execution roles, service roles, cross-account access, Lake Formation, SSO/SAML
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
DESIRED SKILLS:
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
==
==
Calance Consultant Benefits Offerings:
- EPO/PPO Medical Plans
- HMO/PPO Dental programs
- Vision - VSP (Vision Plan Summary)
- 401K Retirement vesting program (VOYA)
- Paid Bi-Weekly/Direct Deposit
- Flex Spending Plan
- Voluntary Life, AD&D, STD or LTD plans