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Aws Machine Learning Jobs (NOW HIRING)

TekCommands Inc

AWS + Generative AI Engineer

Chicago, IL · On-site

$66.75 - $87.50/hr

The ideal candidate will have expertise in AWS Machine Learning, AWS Bedrock, Data Pipelines, AWS Config, and cloud-native architectures . This role involves building enterprise AI solutions ...

Givzey

Machine Learning Engineer

AWS Certified Machine Learning - Specialty or AWS Certified Big Data - Specialty * Experience with AWS machine learning services * Proficiency in using AWS big data services * Knowledge of serverless ...

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How much do aws machine learning jobs pay per hour?

As of Jul 25, 2026, the average hourly pay for aws machine learning in the United States is $70.06, according to ZipRecruiter salary data. Most workers in this role earn between $62.26 and $81.73 per hour, depending on experience, location, and employer.

What is an AWS Machine Learning job?

An AWS Machine Learning job involves designing, building, and deploying machine learning models using Amazon Web Services (AWS) cloud infrastructure. Professionals in this role work with services like Amazon SageMaker, AWS Lambda, and AWS Glue to develop AI-driven applications. They optimize models for scalability, integrate them into cloud-based systems, and ensure efficient data processing. Strong knowledge of machine learning algorithms, AWS architecture, and MLOps best practices is essential for success in this role.

What are the key skills and qualifications needed to thrive in the Aws Machine Learning position, and why are they important?

To thrive as an AWS Machine Learning professional, you need a strong understanding of machine learning principles, proficiency in programming languages like Python, and experience with AWS cloud services such as SageMaker. AWS Certified Machine Learning certification and familiarity with data pipelines, EC2, and Lambda are commonly required. Strong problem-solving, communication, and teamwork skills help you translate business requirements into technical solutions and collaborate effectively with diverse stakeholders. These skills are essential to efficiently deploy and manage scalable machine learning models that deliver business value in cloud-based environments.

What are some typical responsibilities for someone working in an AWS Machine Learning role?

In an AWS Machine Learning position, you'll typically design, develop, and deploy machine learning models using AWS services like SageMaker, Glue, and Lambda. Daily tasks often include data preprocessing, building and training models, and optimizing performance for production environments. You'll collaborate closely with data engineers, software developers, and business analysts to translate business needs into technical solutions. The role may also involve monitoring deployed models, managing cloud resources, and staying updated on new AWS features to ensure efficient and scalable machine learning workflows.

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Aws Machine Learning jobs near you
Infographic showing various Aws Machine Learning job openings in the United States as of July 2026, with employment types broken down into 94% Full Time, 1% Part Time, and 5% Contract. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution, with an average salary of $145,725 per year, or $70.1 per hour.
AWS + Generative AI Engineer

AWS + Generative AI Engineer

TekCommands Inc

Chicago, IL • On-site

$66.75 - $87.50/hr

Contractor

Posted 9 days ago

Job description

We are looking for an experienced AWS + Generative AI Engineer to design and develop secure, scalable, and AI-powered cloud solutions on AWS. The ideal candidate will have expertise in AWS Machine Learning, AWS Bedrock, Data Pipelines, AWS Config, and cloud-native architectures. This role involves building enterprise AI solutions, developing data pipelines, and collaborating with cross-functional teams to deliver innovative cloud applications.

Top 3 Required Skills

  1. AWS Cloud & Machine Learning
  2. AWS Bedrock & Generative AI
  3. AWS Data Pipelines & Infrastructure Automation

Key Responsibilities

  • Design and develop cloud-native applications using AWS services.
  • Build and deploy Generative AI solutions using AWS Bedrock.
  • Design and implement machine learning workflows, model deployment, and monitoring.
  • Develop scalable data pipelines for analytics and AI workloads.
  • Configure and manage AWS Config and governance policies to ensure security and compliance.
  • Design secure, reliable, and cost-effective AWS architectures.
  • Collaborate with data engineers, data scientists, and application teams to deliver AI-powered solutions.
  • Implement Infrastructure as Code (IaC) and cloud automation.
  • Optimize AWS environments for performance, scalability, and cost.
  • Document architecture, technical designs, and best practices.
  • Mentor engineering teams on AWS and Generative AI technologies.

Required Skills

  • 12–16 years of experience in Cloud Engineering, Solution Architecture, or Enterprise Architecture.
  • Strong hands-on experience with Amazon Web Services (AWS).
  • Experience with:
    • AWS Bedrock
    • AWS Machine Learning Services
    • AWS Data Pipeline or similar orchestration tools
    • AWS Config
  • Strong knowledge of Generative AI and Large Language Models (LLMs).
  • Experience designing cloud-native and distributed applications.
  • Experience with Infrastructure as Code (Terraform or CloudFormation).
  • Strong understanding of cloud security, governance, and identity management.
  • Excellent communication and stakeholder management skills.

Preferred Skills

  • Experience with AWS-based commerce platforms.
  • Knowledge of AI/ML model deployment and lifecycle management.
  • Experience with cloud automation and DevOps practices.
  • Experience with Python or other scripting languages.

Certifications

  • AWS Certified Solutions Architect – Professional or
  • AWS Certified Machine Learning – Specialty or equivalent AWS certification