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Amazon Sagemaker Jobs in Texas (NOW HIRING)

IVID TEK INC

MLOps Platform Engineer (SageMaker)

Plano, TX · On-site

$90 - $95/hr

... in Amazon SageMaker (Studio, Pipelines, Model Registry, Endpoints, Feature Store) * 3+ years building and operating production MLOps pipelines -- training, versioning, deployment, monitoring ...

Posted today

Ascentt

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137K/yr

Utilize Amazon SageMaker or similar platforms for building, training, and deploying models in a production-grade environment. * Collaborate closely with data engineers, data scientists, and product ...

Ascentt

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137K/yr

Utilize Amazon SageMaker or similar platforms for building, training, and deploying models in a production-grade environment. * Collaborate closely with data engineers, data scientists, and product ...

B12 Consulting

MLOps

Plano, TX · On-site

... Amazon SageMaker (Studio Classic Studio, Pipelines, Model Registry, Endpoints, Feature Store) o 3+ years building and operating production MLOps pipelines -- training, versioning, deployment ...

Tiger Analytics

Lead Data Engineer - AWS

Dallas, TX · On-site

$113K - $136K/yr

Architect data pipelines using Amazon Bedrock and Amazon SageMaker to build, deploy, and scale Generative AI applications • Vector Foundations: Implement and optimize vector search capabilities ...

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All JobsAmazon Sagemaker JobsAmazon Sagemaker Jobs in Texas

Amazon Sagemaker information

See Texas salary details

$21.4K

$71.9K

$113.7K

How much do amazon sagemaker jobs pay per year?

As of Jul 31, 2026, the average yearly pay for amazon sagemaker in Texas is $71,858.00, according to ZipRecruiter salary data. Most workers in this role earn between $54,000.00 and $89,400.00 per year, depending on experience, location, and employer.

What are Amazon SageMaker training jobs?

Amazon SageMaker training jobs are processes that train machine learning models using specified datasets and algorithms within the SageMaker environment. They involve configuring training parameters, selecting instance types, and monitoring progress through the SageMaker console or APIs. These jobs enable scalable, managed training for developing accurate models efficiently.

What is Amazon SageMaker?

Amazon SageMaker is a fully managed machine learning service provided by AWS that allows developers and data scientists to build, train, and deploy machine learning models quickly and at scale. It offers a range of tools for every stage of the ML workflow, including data labeling, model training, tuning, and deployment. SageMaker supports popular ML frameworks and integrates with other AWS services, making it easier to operationalize machine learning in the cloud. Its managed infrastructure helps reduce the time and complexity involved in developing ML solutions.

What are some common challenges faced by professionals working with Amazon SageMaker, and how can they be addressed?

Professionals working with Amazon SageMaker often encounter challenges such as managing large datasets, optimizing model training costs, and integrating SageMaker with other AWS services or existing data pipelines. Addressing these challenges typically involves leveraging SageMaker's built-in data preprocessing features, using managed spot training to reduce costs, and collaborating closely with data engineering and DevOps teams to ensure seamless integration. Regularly reviewing AWS documentation and best practices can also help professionals stay updated on new features and solutions.

What is the purpose of Amazon SageMaker processing jobs?

Amazon SageMaker processing jobs are used by data scientists and machine learning engineers to perform data preprocessing, feature engineering, model evaluation, and inference tasks at scale. These jobs enable efficient data handling and model validation within the SageMaker environment, supporting the development and deployment of machine learning models.

Are AWS jobs still in demand?

Amazon SageMaker jobs and other AWS roles remain in demand due to the growing adoption of cloud computing and machine learning. Skills in cloud services, data analysis, and AI tools are highly sought after, with many organizations expanding their cloud infrastructure and AI capabilities.

What are the key skills and qualifications needed to thrive as an Amazon SageMaker Machine Learning Engineer, and why are they important?

To excel as an Amazon SageMaker Machine Learning Engineer, you need strong expertise in machine learning concepts, data preprocessing, and programming languages such as Python, along with a degree in computer science or a related field. Familiarity with AWS SageMaker, cloud infrastructure, version control systems like Git, and relevant certifications such as AWS Certified Machine Learning – Specialty are highly beneficial. Exceptional problem-solving, communication, and collaboration skills help you work effectively with cross-functional teams and stakeholders. These skills are vital for building, deploying, and maintaining scalable machine learning solutions that drive business value.

What can I do with Amazon SageMaker?

Amazon SageMaker is a cloud-based machine learning platform that allows data scientists and developers to build, train, and deploy machine learning models at scale. It provides tools for data labeling, model tuning, and deployment, enabling efficient development of AI solutions. Users can also utilize built-in algorithms and integrate with other AWS services for comprehensive machine learning workflows.
What are popular job titles related to Amazon Sagemaker jobs in Texas? For Amazon Sagemaker jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Amazon Sagemaker jobs in Texas look for? The top searched job categories for Amazon Sagemaker jobs in Texas are:
Amazon Sagemaker jobs near you
Infographic showing various Amazon Sagemaker job openings in Texas as of July 2026, with employment types broken down into 58% Full Time, 7% Temporary, and 35% Contract. Highlights an 80% In-person, and 20% Remote job distribution, with an average salary of $71,858 per year, or $34.5 per hour.

MLOps Platform Engineer (SageMaker)

IntelliPro Group Inc.

Plano, TX • On-site

Contractor

Re-posted 13 days ago

Job description

Job title: MLOps Platform Engineer (SageMaker)
Location: Plano TX - Hybrid
Duration: 12-Month Contract (Extension Possible)
Pay Rate: $100/hr. - $102/hr. on  W2
Job Summary
  • We are seeking an experienced MLOps Platform Engineer to support the Enterprise Analytical Data & Integration Team.
  • The ideal candidate will have strong expertise in AWS and Amazon SageMaker, with hands-on experience building and managing production MLOps platforms and ML lifecycle automation.
Key Responsibilities
  • Build and maintain MLOps platforms using AWS SageMaker.
  • Develop and manage ML pipelines for training, deployment, monitoring, and model versioning.
  • Configure and support SageMaker Studio Classic (required) and Unified Studio (preferred).
  • Manage SageMaker Pipelines, Model Registry, Feature Store, Endpoints, and MLflow.
  • Collaborate with data scientists and engineering teams to deliver scalable ML solutions.
Required Qualifications
  • 10–15 years of software engineering experience in cloud infrastructure or MLOps.
  • 5+ years of hands-on AWS experience with deep expertise in Amazon SageMaker.
  • 3+ years of production MLOps pipeline experience.
  • Experience with SageMaker Studio Classic (mandatory), Unified Studio (preferred), MLflow, and Airflow or AWS Step Functions.
  • Strong communication and problem-solving skills.
Must-Have Skills
  • AWS
  • Amazon SageMaker (Studio Classic)
  • SageMaker Pipelines
  • Model Registry & Feature Store
  • MLflow
  • Airflow / AWS Step Functions
  • Production MLOps Pipelines

About Us:
Founded in 2009, IntelliPro is a global leader in talent acquisition and HR solutions. Our commitment to delivering unparalleled service to clients, fostering employee growth, and building enduring partnerships sets us apart. We continue leading global talent solutions with a dynamic presence in over 160 countries, including the USA, China, Canada, Singapore, Japan, Philippines, UK, India, Netherlands, and the EU.
IntelliPro, a global leader connecting individuals with rewarding employment opportunities, is dedicated to understanding your career aspirations. As an Equal Opportunity Employer, IntelliPro values diversity and does not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, genetic information, disability, or any other legally protected group status. Moreover, our Inclusivity Commitment emphasizes embracing candidates of all abilities and ensures that our hiring and interview processes accommodate the needs of all applicants. Learn more about our commitment to diversity and inclusivity at https://intelliprogroup.com/.
Compensation: The pay offered to a successful candidate will be determined by various factors, including education, work experience, location, job responsibilities, certifications, and more. Additionally, IntelliPro provides a comprehensive benefits package, all subject to eligibility.
 

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