Senior AI Engineer – Search, Personalization, Agents

Hyatt

. Build and operate production AI systems improving Hyatt’s search, personalization, guest experiences, colleague productivity, and operational workflows .

Posted 9/25/2026full-timeRemote • Illinois • United StatesSenior💰 $133,200 - $173,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in building and deploying Generative AI solutions, particularly in natural language processing and recommender systems, while applying responsible AI practices and effective model evaluation frameworks. Proficient in collaborating with cross-functional teams to deliver scalable machine learning systems and communicate complex model behaviors to diverse audiences.

Highest-signal resume keywords

Machine Learning ExpertiseGenerative AI SolutionsAWS Cloud ServicesPython ProgrammingData Pipeline Design

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Machine LearningNatural Language ProcessingRecommender SystemsModel Evaluation FrameworksData Science Problem TranslationModel Lifecycle ManagementSQLPySparkContainerizationCI/CD

Soft Skills

Interpersonal SkillsCommunication Skills

Tools & Technologies

AWS SageMakerAWS ECS/EKSAWS Step FunctionsAWS LambdaAWS GlueDocker

Certifications & Qualifications

Master's Degree in Computer SciencePh.D Preferred

Industry Keywords

Responsible AIAgile Development PracticesML ObservabilityBias and Safety ChecksRetrieval-Augmented Generation

Tech Stack

Tools & technologies

AWSCloudDockerPySparkPythonSQL

About the role

Key responsibilities & impact

Build and operate production AI systems improving Hyatt’s search, personalization, guest experiences, colleague productivity, and operational workflows
Design, prototype, and productionize Generative AI solutions in natural-language search, information retrieval, and recommender systems
Build and evaluate LLM-powered applications using retrieval-augmented generation, prompt engineering, fine-tuning, embeddings, semantic search, and agentic or workflow-based AI systems
Develop model evaluation frameworks covering offline metrics, human evaluation, guardrail testing, bias and safety checks, and business-impact measurement
Translate ambiguous business problems into data science problem statements, solution designs, success metrics, and implementation plans
Lead solution design, modeling decisions, experimentation strategy, and technical tradeoff discussions
Partner with ML and data engineering teams to deploy scalable real-time inference pipelines and batch processing workflows
Influence technical roadmaps and sequence data science initiatives
Collaborate on design reviews, code reviews, ML engineering best practices, and knowledge sharing
Productionize models and AI services using AWS-native tools and modern MLOps practices
Contribute to data pipelines, feature workflows, model serving, observability, monitoring, and lifecycle management
Apply version control, CI/CD, testing, reproducibility, containerization, and documentation
Support batch and low-latency inference deployments
Work with product owners, ML scientists, ML engineers, data engineers, architects, and business stakeholders to deliver end-to-end algorithmic products
Communicate model behavior, limitations, assumptions, risks, and business impact to technical and non-technical audiences
Define measurable success criteria and evaluate AI outcomes
Champion responsible AI, inclusive design, and practical experimentation

Requirements

What you’ll need

Master’s degree in computer science, Software Engineering, or related field
4+ years of experience in machine learning roles focused on NLP/NLU, recommender systems, or LLM applications
Experience deploying LLMs or other Generative AI solutions to production
Expertise in AWS cloud services, including SageMaker, ECS/EKS, Step Functions, Lambda, and Glue
Strong programming skills in Python
Experience with SQL, PySpark, and containerization such as Docker
4+ years of experience designing scalable data pipelines and ML systems for real-time and batch inference
Familiarity with ML observability and governance tools
Solid understanding of responsible AI practices, CI/CD pipelines, Agile development practices, and model lifecycle management
Excellent interpersonal and communication skills
Ph.D preferred

Benefits

Comp & perks

Annual allotment of free hotel stays at Hyatt hotels globally
Flexible work schedule
Work-life benefits including wellbeing initiatives such as a complimentary Headspace subscription
Discount at the on-site fitness center
Global family assistance policy with paid time off following the birth or adoption of a child
Financial assistance for adoption
Paid Time Off
Medical
Dental
Vision
401K with company match