Senior Machine Learning / MLOps Engineer (Remote Opportunity)

Senior Machine Learning / MLOps Engineer (Remote Opportunity) US - IL - Chicago Technology Professional Staff/Corporate Full-time Yearly US Dollar (USD) pay basis Summary Hyatt Hotels Corporation seeks an enthusiastic Senior ML Engineer to join our Data Science and Machine Learning department. In this role, you will collaborate closely with the broader Data and Analytics team and help continue to make Hyatt a leading hospitality company. Benefits Annual allotment of free hotel stays at Hyatt hotels globally Work‑life benefits including wellbeing initiatives such as a complimentary Headspace subscription, and a discount at the on‑site fitness center A global family assistance policy with paid time off following the birth or adoption of a child as well as financial assistance for adoption Paid Time Off, Medical, Dental, Vision, 401K with company match 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. Qualifications Experience Required 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, with a focus on AI services and MLOps foundations. Demonstrated 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 Preferred 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. The salary range for this position is $133,200 - $173,000. The final pay rate/salary offered to the successful candidate will depend on experience, skill level, and other qualifications for the role, as well as the location of the performance of work. Pay for the successful candidate will meet local requirements, including the local minimum wage rate. #J-18808-Ljbffr