Senior Machine Learning Engineer

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🕒 June 11

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Hyatt

WebsiteLinkedInAll Job Openings

10,000+ employees

🍽️ Food & Beverage

✈️ Travel

🛒 Retail

Food & Beverage • Travel • Retail

Hyatt is a global hospitality company that operates a range of hotels, resorts, and vacation properties. Known for its commitment to providing exceptional guest experiences, Hyatt offers various accommodation options, from luxury to more affordable stays. The company also focuses on sustainability and community engagement, ensuring responsible business practices in the hospitality sector.

📋 Description

• Design and implement end-to-end ML systems, including data ingestion, feature processing, model training, and model serving • Architect and deploy scalable AI services for real-time and batch inference use cases • Build and maintain ML infrastructure across cloud environments, including EC2, EKS, SageMaker, and specialized inference hardware • Develop and evolve MLOps platforms, including training pipelines, deployment workflows, feature stores, and model observability • Implement CI/CD and infrastructure-as-code patterns to automate model lifecycle management • Optimize model training and inference performance for cost, latency, and hardware efficiency • Monitor production ML systems for accuracy, reliability, and operational health • Partner with data engineering, architecture, governance, and security teams on compliant and scalable solutions • Mentor team members on ML engineering, system design, and operational best practices • Contribute to initiatives advancing AI platform maturity and engineering standards

🎯 Requirements

• Master’s degree in Computer Science, Software Engineering, Machine Learning, or a related field • 5+ years of experience building and operating machine learning solutions in cloud environments, focused on AI services and MLOps foundations • Hands-on experience delivering end-to-end ML systems spanning model development, deployment, and production infrastructure • Proficiency with modern ML engineering tooling, including cloud platforms, data pipelines, and CI/CD workflows • Experience designing and scaling real-time and batch inference systems in production • Hands-on experience with deep learning frameworks and model optimization for performance and cost • Experience building or contributing to shared MLOps platforms, feature stores, or ML observability solutions • Familiarity with cloud security, governance, and compliance standards

🏖️ Benefits

• Annual allotment of free hotel stays at Hyatt hotels globally • Flexible work schedule • Paid Time Off • Medical