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Amazon Sagemaker Jobs in Texas (NOW HIRING)

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 ...

AI Ops

Dallas, TX · On-site

$129K - $165K/yr

... in Amazon SageMaker.( Must) * 3+ years building and operating production MLOps pipelines.( Must) * Experience with SageMaker Unified Studio or Studio Classic. * MLflow or equivalent experiment ...

Lead Data Engineer - AWS

Dallas, TX · On-site +1

$101K - $133K/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 ...

Lead Data Engineer - AWS

Dallas, TX · On-site

$101K - $133K/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 ...

AI/ML Engineer

Plano, TX · On-site

$120 - $160/hr

Experience with model-serving infrastructure, such as Amazon SageMaker, NVIDIA Triton, Ray Serve, or similar platforms. * Hands-on experience with GenAI libraries and frameworks, including LangChain ...

AI/ML Engineer

Plano, TX · On-site

$65 - $75/hr

Experience with model-serving infrastructure, such as Amazon SageMaker, NVIDIA Triton, Ray Serve, or similar platforms. * Hands-on experience with GenAI libraries and frameworks, including LangChain ...

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

Showing results 21-40

Amazon Sagemaker information

See Texas salary details

$21.4K

$71.9K

$113.7K

How much do amazon sagemaker jobs pay per year?

As of Sep 6, 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 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 the key skills and qualifications needed to thrive as an Amazon SageMaker machine learning engineer?

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 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 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 efficiently. It provides tools for data labeling, model tuning, and deployment, supporting various frameworks like TensorFlow and PyTorch. Users can automate workflows, manage models at scale, and integrate with other AWS services for end-to-end machine learning solutions.

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:

Infographic showing various Amazon Sagemaker job openings in Texas as of August 2026, with employment types broken down into 91% Full Time, 6% Part Time, and 3% Contract. Highlights an 84% Physical, 6% Hybrid, and 10% Remote job distribution, with an average salary of $71,858 per year, or $34.5 per hour.

Cyber - AWS Forward Deployed Security Engineer (FDE) - Senior Consultant

Deloitte

San Antonio, TX • On-site

$103K - $141K/yr

Full-time

Posted 19 days ago


Key responsibilities

  • Embed directly with client cloud and platform engineering teams to design, build, deploy, and operate automated security controls across AWS environments.

  • Design and implement security guardrails for AWS generative AI and machine learning services, containerized, and serverless workloads.

  • Build automated data protection and data loss prevention capabilities using AWS security services and encryption patterns.


Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 93 frontline employees who took The Breakroom Quiz

47th of 154 rated financial services


Job description

Join Deloitte's Cloud Cyber Risk practice as a Forward Deployed Security Engineer and help organizations secure their Amazon Web Services (AWS) cloud and AI workloads at scale while working directly with client engineering teams. This is not an assessment-and-handoff role. You will design, build, deploy, and operate secure-by-default AWS environments and automated security controls across generative AI services, container and data platforms, infrastructure-as-code, and secure delivery pipelines. This role is designed for a hands-on engineer who enjoys solving complex cloud security challenges, building working automation, and supporting security outcomes in production environments.

Recruiting for this role ends on 12/31/2026.

Work you'll do

As an Engineering and Product Engineer III on the Cloud Cyber Risk team, you will be responsible for:

  • Embed directly with client cloud and platform engineering teams to design, build, deploy, and operate automated security controls across AWS environments from initial design through production support.
  • Design and implement security guardrails for AWS generative artificial intelligence (AI) and machine learning services, including Amazon Bedrock, Amazon Bedrock AgentCore, and Amazon SageMaker, as well as containerized and serverless workloads on Amazon Elastic Kubernetes Service (EKS).
  • Build automated data protection and data loss prevention capabilities using Amazon Macie, AWS Key Management Service (KMS), and encryption and tokenization patterns across Amazon Simple Storage Service (S3), databases, and analytics platforms.
  • Deploy and maintain AWS-native security services, including AWS Security Hub, Amazon GuardDuty, AWS Config, AWS Identity and Access Management (IAM) Access Analyzer, and AWS CloudTrail, within client monitoring and security operations workflows.
  • Write and maintain production infrastructure-as-code using Terraform and/or AWS CloudFormation, integrate security scanning into continuous integration / continuous deployment (CI/CD) pipelines, and contribute reusable modules, runbooks, and reference implementations for future engagements.

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

The team

Deloitte's Cloud Cyber Risk team helps organizations pursue growth, innovation, and performance through proactive management of cyber risk. Our Forward Deployed Security Engineers work directly within client teams, combining risk, regulatory, and technology capabilities with hands-on engineering to design, build, and operate scalable, automated AWS cloud security solutions. This team works closely with clients to implement controls in production environments and support security outcomes at scale.

Qualifications

Required:

  • 5+ years of experience in cloud security, cybersecurity, technology risk, or technology consulting; and a bachelor's degree in computer science, cybersecurity, information technology, engineering, or a technical field
  • 3+ years of hands-on experience designing, building, or operating security solutions in Amazon Web Services (AWS) production environments, including AWS Security Hub, Amazon GuardDuty, AWS Config, AWS Identity and Access Management (IAM), AWS Key Management Service (KMS), and AWS CloudTrail
  • 2+ years of experience using Terraform and/or AWS CloudFormation to deploy infrastructure and security controls through production deployment pipelines
  • Experience securing at least one of the following in a production environment: Amazon Elastic Kubernetes Service (EKS) / containers, Amazon SageMaker or Amazon Bedrock workloads, or data protection using Amazon Macie
  • Experience integrating security controls into continuous integration / continuous deployment (CI/CD) pipelines, including static application security testing (SAST), dynamic application security testing (DAST), software composition analysis (SCA), secrets scanning, and infrastructure-as-code (IaC) scanning; experience scripting in Python, Bash, or Go to automate enforcement or remediation; and experience working directly with client or customer engineering teams in onsite or virtual delivery environments
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Limited immigration sponsorship may be available.

Preferred:

  • Experience securing generative AI and agentic workloads on Amazon Bedrock, Amazon Bedrock AgentCore, or Amazon SageMaker in production environments
  • Experience using policy-as-code and guardrail tools, including AWS Service Control Policies, Open Policy Agent, Checkov, or tfsec
  • Experience with AWS Control Tower, secure landing zones, and multi-account governance
  • Experience with Kubernetes security tooling and runtime protection
  • Experience implementing security controls aligned to International Organization for Standardization (ISO) 27001, National Institute of Standards and Technology Cybersecurity Framework (NIST CSF), National Institute of Standards and Technology Special Publication 800-53 (NIST SP 800-53), Payment Card Industry Data Security Standard (PCI DSS), or System and Organization Controls 2 (SOC 2)
  • Prior experience in a forward-deployed, startup, or professional services delivery model; AWS Certified Security - Specialty, AWS Certified Solutions Architect, or Certified Cloud Security Professional (CCSP)

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $134,500 to $265,100.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Qualifications:

Join Deloitte's Cloud Cyber Risk practice as a Forward Deployed Security Engineer and help organizations secure their Amazon Web Services (AWS) cloud and AI workloads at scale while working directly with client engineering teams. This is not an assessment-and-handoff role. You will design, build, deploy, and operate secure-by-default AWS environments and automated security controls across generative AI services, container and data platforms, infrastructure-as-code, and secure delivery pipelines. This role is designed for a hands-on engineer who enjoys solving complex cloud security challenges, building working automation, and supporting security outcomes in production environments.

Recruiting for this role ends on 12/31/2026.

Work you'll do

As an Engineering and Product Engineer III on the Cloud Cyber Risk team, you will be responsible for:

  • Embed directly with client cloud and platform engineering teams to design, build, deploy, and operate automated security controls across AWS environments from initial design through production support.
  • Design and implement security guardrails for AWS generative artificial intelligence (AI) and machine learning services, including Amazon Bedrock, Amazon Bedrock AgentCore, and Amazon SageMaker, as well as containerized and serverless workloads on Amazon Elastic Kubernetes Service (EKS).
  • Build automated data protection and data loss prevention capabilities using Amazon Macie, AWS Key Management Service (KMS), and encryption and tokenization patterns across Amazon Simple Storage Service (S3), databases, and analytics platforms.
  • Deploy and maintain AWS-native security services, including AWS Security Hub, Amazon GuardDuty, AWS Config, AWS Identity and Access Management (IAM) Access Analyzer, and AWS CloudTrail, within client monitoring and security operations workflows.
  • Write and maintain production infrastructure-as-code using Terraform and/or AWS CloudFormation, integrate security scanning into continuous integration / continuous deployment (CI/CD) pipelines, and contribute reusable modules, runbooks, and reference implementations for future engagements.

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

The team

Deloitte's Cloud Cyber Risk team helps organizations pursue growth, innovation, and performance through proactive management of cyber risk. Our Forward Deployed Security Engineers work directly within client teams, combining risk, regulatory, and technology capabilities with hands-on engineering to design, build, and operate scalable, automated AWS cloud security solutions. This team works closely with clients to implement controls in production environments and support security outcomes at scale.

Qualifications

Required:

  • 5+ years of experience in cloud security, cybersecurity, technology risk, or technology consulting; and a bachelor's degree in computer science, cybersecurity, information technology, engineering, or a technical field
  • 3+ years of hands-on experience designing, building, or operating security solutions in Amazon Web Services (AWS) production environments, including AWS Security Hub, Amazon GuardDuty, AWS Config, AWS Identity and Access Management (IAM), AWS Key Management Service (KMS), and AWS CloudTrail
  • 2+ years of experience using Terraform and/or AWS CloudFormation to deploy infrastructure and security controls through production deployment pipelines
  • Experience securing at least one of the following in a production environment: Amazon Elastic Kubernetes Service (EKS) / containers, Amazon SageMaker or Amazon Bedrock workloads, or data protection using Amazon Macie
  • Experience integrating security controls into continuous integration / continuous deployment (CI/CD) pipelines, including static application security testing (SAST), dynamic application security testing (DAST), software composition analysis (SCA), secrets scanning, and infrastructure-as-code (IaC) scanning; experience scripting in Python, Bash, or Go to automate enforcement or remediation; and experience working directly with client or customer engineering teams in onsite or virtual delivery environments
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Limited immigration sponsorship may be available.

Preferred:

  • Experience securing generative AI and agentic workloads on Amazon Bedrock, Amazon Bedrock AgentCore, or Amazon SageMaker in production environments
  • Experience using policy-as-code and guardrail tools, including AWS Service Control Policies, Open Policy Agent, Checkov, or tfsec
  • Experience with AWS Control Tower, secure landing zones, and multi-account governance
  • Experience with Kubernetes security tooling and runtime protection
  • Experience implementing security controls aligned to International Organization for Standardization (ISO) 27001, National Institute of Standards and Technology Cybersecurity Framework (NIST CSF), National Institute of Standards and Technology Special Publication 800-53 (NIST SP 800-53), Payment Card Industry Data Security Standard (PCI DSS), or System and Organization Controls 2 (SOC 2)
  • Prior experience in a forward-deployed, startup, or professional services delivery model; AWS Certified Security - Specialty, AWS Certified Solutions Architect, or Certified Cloud Security Professional (CCSP)

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $134,500 to $265,100.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Education:Bachelor's DegreeEmployment Type:

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