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AI/ML Engineer, AWS

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. Build and deliver scalable systems that incorporate machine learning and Generative AI capabilities.

Posted 4/22/2026full-timeChicago • Illinois • 🇺🇸 United StatesMid-LevelSenior💰 $120,000 - $155,000 per yearWebsite

Tech Stack

Tools & technologies
AWSPython

About the role

Key responsibilities & impact
  • Build and deliver scalable systems that incorporate machine learning and Generative AI capabilities.
  • Create, evaluate, and deploy machine learning solutions, including applications powered by large language models.
  • Establish and maintain datasets, testing strategies, and validation approaches to ensure model accuracy and stability.
  • Partner with product and engineering teams to translate business needs into practical, deployable AI solutions.
  • Integrate machine learning components into existing platforms and services.
  • Develop and manage automated pipelines that support continuous integration and delivery of machine learning solutions.
  • Monitor performance in production environments and refine systems based on real-world usage.

Requirements

What you’ll need
  • Must be US Citizen or green card holder
  • Bachelor’s degree in Computer Science, Engineering, or related field.
  • 3 years experience delivering machine learning or AI-based solutions in production settings.
  • 3 years experience programming in Python or a comparable language.
  • 3 years experience working with large language models or Generative AI technologies.
  • 3 years experience building and deploying solutions in AWS environments.
  • 3 years experience establishing automated build, test, and release workflows for ML or data-driven applications.
  • 3 years experience supporting deployed models, including monitoring performance and managing updates.

Benefits

Comp & perks
  • Health insurance
  • Flexible work arrangements
  • Professional development opportunities

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools
machine learningGenerative AIlarge language modelsPythonAWSautomated pipelinescontinuous integrationcontinuous deliverymodel monitoringdata validation