Senior ML Engineer: Real-Time AI & MLOps

Hyatt Hotels Corporation; Chicago (IL); À distance; USD 150 000 - 180 000; Plein temps

Résumé du poste

Hyatt Hotels Corporation is seeking a Senior ML Engineer to join our Data Science and Machine Learning team in Chicago. You will collaborate with data science, data engineering, and platform teams to design, build, and operate scalable AI services that translate models into production-grade systems.

You will contribute to cross-functional initiatives advancing our AI platform capabilities, mentoring colleagues, and ensuring reliable performance across cloud environments.

Qualifications

• Master’s degree in Computer Science or related field.
• 5+ years of experience building and operating ML solutions in cloud environments.
• Hands-on experience delivering end-to-end ML systems, deployment, and production infrastructure.
• Proficiency with ML tooling, cloud platforms, data pipelines, and CI/CD.

Responsabilités

• Design and build end-to-end ML systems with data ingest, feature processing, model training, and serving.
• Architect and deploy scalable AI services for real-time and batch inference.
• Develop ML infrastructure across cloud environments and optimize performance/cost.
• Advance MLOps platforms, pipelines, feature stores, and observability.
• Implement CI/CD and IaC to automate model lifecycle management.

Connaissances

Machine learning

MLOps

Cloud platforms

CI/CD

Model deployment

Formation

Master’s degree in Computer Science or related field

Outils

SageMaker

EC2

EKS

CI/CD pipelines

Description du poste

Hyatt Hotels Corporation is seeking a Senior ML Engineer to join our Data Science and Machine Learning team in Chicago. You will collaborate with data science, data engineering, and platform teams to design, build, and operate scalable AI services that translate models into production-grade systems.

You will contribute to cross-functional initiatives advancing our AI platform capabilities, mentoring colleagues, and ensuring reliable performance across cloud environments.