MLOps Platform Engineer (SageMaker)

Russell Tobin; Plano (TX); On-site; USD 110,000 - 131,000; Full time

Benefits offered by this job

Healthcare coverage and benefits

401(k) Retirement Savings

Life & Disability Insurance

Employee discounts and programs

Job summary

Russell Tobin is seeking a Senior ML Platform Engineer to design, build, and operationalize an enterprise ML platform on AWS SageMaker Unified Studio in Plano, TX. The role covers the full ML lifecycle from data discovery through deployment and monitoring.

You will migrate to a unified, governed platform on AWS Landing Zone 2, with domain/project setup, multi-tenant configuration, and robust observability. The contract is 12 months with extension, onsite in Plano.

Qualifications

• 10-15 years software engineering in cloud infra or ML platform operations.
• 5+ years AWS with SageMaker (Studio, Pipelines, Registry, Endpoints, Feature Store).
• 3+ years in production MLOps pipelines: training, versioning, deployment, monitoring.

Responsibilities

• Set up SageMaker Unified Studio platform with multi-environment promotion workflows.
• Build MLOps pipelines for data extraction, preprocessing, training, evaluation, and model registration.
• Manage SageMaker Model Registry with cross-account promotion, versioning, and lineage tracking.
• Configure MLflow experiment tracking with auto-logging of params, metrics and artifacts.
• Set up IAM including Okta SSO, SailPoint entitlements and execution roles for pipelines.
• Build model serving with real-time endpoints and batch prediction workflows.
• Set up model monitoring for data/model drift and performance degradation.
• Configure data catalog with searchable datasets and lineage tracking.
• Own platform operations including observability (CloudWatch, Datadog) and logging.

Skills

SageMaker

MLOps pipelines

AWS

Terraform / CDK

Kubernetes

Tools

SageMaker Studio

Snowflake

MLflow

Terraform

Kubernetes (EKS)

Job description

Job Title: MLOps Platform Engineer (SageMaker)

Location: Plano, TX (Onsite)

Duration: 12 Months contract with extension

Pay Range: $80-$95/hr on W2 (DOE)

What we’re 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

Equal Employment Opportunity

PrideGlobal and it's affiliates are an equal opportunity employer. We do not discriminate on the basis of the race, religious creed, color, national origin, ancestry, physical disability, mental disability, reproductive health decision making, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, age, sexual orientation, veteran or military status, or any other characteristic protected by applicable federal, state, or local law.

Fair Chance Employment

PrideGlobal and it's affiliates are a Fair Chance employer. We consider all qualified applicants, including those with criminal histories, in a manner consistent with applicable state and local Fair Chance laws and ordinances, including, the California Fair Chance Act and all applicable local Fair Chance ordinances.

Accommodations

We are committed to providing reasonable accommodations to applicants and employees with disabilities. If you require a reasonable accommodation to participate in the application or interview process, or to perform the essential functions of this role, please contact us.

Only applicable for San Francisco Candidates

Under the San Francisco Lactation in the Workplace Ordinance, we will provide written notice of lactation accommodation rights, and this notice will automatically be given upon hiring, any inquiry of parental leave or lactation accommodation.

Benefits Info

Russell Tobin/Pride Global offers eligible employee’s comprehensive healthcare coverage (medical, dental, and vision plans), supplemental coverage (accident insurance, critical illness insurance and hospital indemnity), 401(k)-retirement savings, life & disability insurance, an employee assistance program, legal support, auto, home insurance, pet insurance and employee discounts with preferred vendors.

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During the recruiting, pre‑offer process and offer process, we may collect the following categories of personal information:

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