Senior AI/ML Platform Engineer - Cloud-Native & Production

Hyatt; Chicago (IL); On-site; USD 133,000 - 173,000; Full time

Job summary

Hyatt Hotels Corporation seeks an enthusiastic Sr. AI/ML Engineer to join our Data and Analytics team in Chicago. You’ll collaborate closely with the ML/AI squad to build scalable platforms and production-ready AI solutions that power Hyatt’s digital experiences.

You will contribute to architecture, Python development, and end-to-end ML pipelines, deploying models and tooling across AWS and GCP. Strong collaboration and a track record delivering reliable services are essential.

Qualifications

• 7+ years of software engineering experience with a focus on AI/ML and cloud-based platforms.
• Experience designing and operating shared platforms used by multiple teams.
• Strong end-to-end system design skills for APIs, data flows, and deployment.
• Production systems experience for AI/ML including model serving and monitoring.
• Ability to work independently on complex technical problems and drive solutions.
• Collaboration across engineering, data, infrastructure, security, and product teams.
• Master’s degree or equivalent practical experience in a technical field.
• Familiarity with AWS and GCP and at least one managed AI service.

Responsibilities

• Build and operate shared AI/ML platforms used by product engineering teams.
• Contribute to architecture, Python development, and problem solving across cloud environments.

Skills

AI engineering

Distributed systems

Python development

End-to-end design

Production services

Cross-functional collaboration

Education

Master’s degree in Computer Science or related field

Tools

AWS

GCP

Docker

Vertex AI / comparable platforms

Datadog / Arize

Job description

Hyatt Hotels Corporation seeks an enthusiastic Sr. AI/ML Engineer to join our Data and Analytics team in Chicago. You’ll collaborate closely with the ML/AI squad to build scalable platforms and production-ready AI solutions that power Hyatt’s digital experiences.

You will contribute to architecture, Python development, and end-to-end ML pipelines, deploying models and tooling across AWS and GCP. Strong collaboration and a track record delivering reliable services are essential.