Plano, TX

Salary
$100–$102/hrfrom the description
Posted
Jul 28, 2026
Location
Plano, TX
Last confirmed open
Jul 29, 2026

What this job asks for AI summary

This is a 12-month W2 contract role on an Enterprise Analytical Data & Integration Team, focused on building and maintaining production MLOps platforms centered on AWS SageMaker. The engineer will develop and manage end-to-end ML pipelines covering training, deployment, monitoring, and model versioning, and will collaborate closely with data scientists. It suits an experienced cloud/MLOps practitioner with deep SageMaker expertise and a track record of shipping production ML infrastructure.

Senior level · 10+ years · Dallas-Fort Worth-Arlington, TX · Contract

Quick apply — this platform usually takes a CV and a few fields.

Must have (8)
AWS · 5+ yrsSageMaker · 5+ yrsSageMaker Studio ClassicSageMaker PipelinesSageMaker Model RegistrySageMaker Feature StoreMLflowAirflow
Nice to have (1)
SageMaker Unified Studio

We read this from the posting text with AI. Skim the description below before ruling yourself out.

How this req sits in the market our data

What gives you an edge
MLflow8%

Rare in this occupation — lead with these, and say what you built with them.

What the occupation pays Median $136,221 (middle half $107,984–$167,709). This posting is about at that midpoint.

Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 29, 2026. It is a model, not a headcount.

Why we read it this way (6)

The role is a 12-month W2 contract with possible extension, placed by staffing firm IntelliPro — the end client is not named.

Airflow and AWS Step Functions are listed together as interchangeable options ('Airflow or AWS Step Functions') under both Required Qualifications and Must-Have Skills, so they are captured as a single requirement with alternatives.

SageMaker Unified Studio is explicitly marked 'preferred' in both the responsibilities and qualifications sections, so it is flagged as preferred.

The 10–15 year overall experience range maps to a minimum of 10 years at the role level. The 3+ years of production MLOps pipeline experience is a role-level gate subsumed by the broader 10-year requirement and is not broken out as a separate skill.

SOC classification is Medium confidence: the role primarily builds and ships ML pipeline software (pointing to 15-1252 Software Developers), but has a meaningful infrastructure/platform operations dimension that could support 15-1244.

Posting is for a contract engagement — the market benchmarks below price full-time roles, so read the comp comparison with that in mind.

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