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MLOps Platform Engineer (SageMaker) - Contract

TalentBurst, Inc.

Plano, TX

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JOB DETAILS
SKILLS
Acceptance Testing, Amazon Web Services (AWS), Autoscaling, Blueprints, Cloud Computing, Consumer Promotions, Data Modeling, Data Quality, Data Sets, Engineering, Identity Data Management, Machine Learning, Metrics, Network Security, Performance Modeling, Private Security, Promotional Programs, Quality Monitoring, Security Assertion Markup Language (SAML), Single Sign-On (SSO), Snowflake Schema, Software Engineering, Systems Administration/Management
LOCATION
Plano, TX
POSTED
1 day ago

Job Title: MLOps Platform Engineer (SageMaker)
Location: Plano TX Onsite
Duration: 12-month contract with possible extension
 
Interview Process:

  • 1st RoundMS Teams Technical Interview – SageMaker and AWS
  • 2nd RoundMS Teams Technical Interview – SageMaker and AWS
 
Must Haves:
  • 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 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 have.
 
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 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

About the Company

T

TalentBurst, Inc.

For over 20 years, TalentBurst Inc. has been an award-winning provider of cutting-edge Workforce Management Solutions. With a strong commitment to staying ahead in the tech landscape, we pioneer innovative approaches to talent acquisition. Our expertise spans Life Sciences, and Healthcare Staffing, Banking, Financial, IT, and Engineering, as well as Global Employer of Record (EOR), Agent of Record (AOR), State, Local Government and Education (SLED), and IC validation/compliance services. Additionally, our division, TalentProcure, leads the industry with offerings such as High Hazard Payroll, Managed Services, and Vendor on Premise (VOP) solutions.

Due to our prioritization of excellent standards, we are Joint Commission Certified and are a certified Minority Business Enterprise (MBE) in the USA and Canada. Supporting over 130 Fortune 500 companies globally, we excel in navigating the landscape of talent acquisition. In a world of constant change, we embrace developing people-centric solutions that address the unique demands of our clients. Stay connected by visiting our website and following us on social media!

 

COMPANY SIZE
5,000 to 9,999 employees
INDUSTRY
Staffing/Employment Agencies
FOUNDED
2002
WEBSITE
http://www.talentburst.com/