Senior Machine Learning Engineer (Remote)

Hyatt

• $130K — $155K *
Hospitality & Recreation
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years of experience in machine learning engineering or related field
  • Strong proficiency in ML frameworks (e.g., TensorFlow, PyTorch)
  • Experience with cloud platforms (e.g., AWS, Azure) and MLOps tools
  • Solid understanding of data engineering principles and practices
  • Proven ability to design and implement scalable AI systems
  • Familiarity with CI/CD and infrastructure-as-code methodologies
  • Excellent communication and collaboration skills

Responsibilities

  • Design and implement end-to-end ML systems, from data ingestion to model serving
  • Architect and deploy scalable AI services for real-time and batch inference
  • Build and maintain ML infrastructure across various cloud environments
  • Develop MLOps platforms, including training pipelines and model observability
  • Implement CI/CD and infrastructure-as-code for model lifecycle management
  • Optimize model performance for cost, latency, and efficiency
  • Monitor production ML systems for accuracy and operational health
  • Collaborate with cross-functional teams to ensure compliant solutions
  • Mentor team members on ML engineering best practices
  • Contribute to initiatives that enhance AI platform maturity

Benefits

  • Opportunity to work in a collaborative and innovative environment
  • Access to continuous learning and skill development
  • Engagement in cross-functional projects that impact the organization
  • Mentorship opportunities within a passionate team
  • Involvement in advancing AI platform capabilities
Full Job Description
The Opportunity

Hyatt Hotels Corporation seeks an enthusiastic Senior ML Engineer to join our Data Science and Machine Learning department. In this role, you will be collaborating closely with the broader Data and Analytics team, where you'll be instrumental in continuing to make Hyatt a leading hospitality company. You will be part of a team that is passionate about our purpose, committed to nurturing curiosity and new skills, and building connections across the organization with colleagues, customers, and guests.

The Role

The Machine Learning Engineer partners with data science, data engineering, and platform teams to design, build, and operate scalable AI services. This role is responsible for translating machine learning models into reliable, production-grade systems through strong infrastructure design, MLOps automation, and performance optimization. The position also contributes to cross-functional initiatives that advance the organization's AI platform capabilities.

Responsibilities
  • Design and implement end-to-end ML systems, including data ingestion, feature processing, model training, and model serving
  • Architect and deploy scalable AI services supporting real-time and batch inference use cases
  • Build and maintain ML infrastructure across cloud environments (e.g., EC2, EKS, SageMaker, 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 cross-functionally with data engineering, architecture, governance, and security teams to ensure compliant and scalable solutions
  • Mentor team members on ML engineering, system design, and operational best practices
  • Contribute to special initiatives that advance AI platform maturity and engineering standards

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