Job Description

Salary: $180,000 - 210,000 per year Requirements:

• We require a masters degree in computer science, software engineering, or a related discipline; a PhD is preferred.
• We look for 6+ years of experience in machine learning roles, particularly in NLP/NLU, reinforcement learning, or LLM-based applications.
• We expect 3+ years of people management experience in a technical leadership setting.
• We need hands-on experience fine-tuning and deploying LLMs or other generative AI solutions into production.
• We require strong expertise with AWS cloud services such as SageMaker, ECS/EKS, Step Functions, Lambda, and Glue.
• We look for advanced programming skills in Python, plus working knowledge of SQL, PySpark, and containerization tools such as Docker.
• We expect experience building scalable data pipelines and ML systems for both real-time and batch inference.
• We value a deep understanding of responsible AI practices, CI/CD pipelines, Agile development methods, and model lifecycle management.
• We require excellent communication and interpersonal skills, along with a strong bias toward action and collaboration.
• Familiarity with ML observability and governance tools is preferred.

• We design, prototype, and operationalize generative AI solutions for natural-language search, information retrieval, and recommender systems.
• We build and assess LLM-powered applications, including retrieval-augmented generation, prompt engineering, fine-tuning, embeddings, semantic search, and agentic or workflow-based AI systems.
• We create robust model evaluation frameworks covering offline metrics, human review, guardrail testing, bias and safety validation, and business impact measurement.
• We identify opportunities to apply AI that improve guest experience, colleague productivity, operational efficiency, and commercial results.
• We convert ambiguous business problems into clear data science problem statements, solution designs, success measures, and implementation plans.
• We act as a hands-on technical lead for high-impact AI and machine learning initiatives.
• We guide solution architecture, modeling choices, experimentation strategy, and technical trade-off discussions.
• We partner with ML engineering and data engineering teams to deliver scalable real-time inference pipelines and batch workflows.
• We help shape technical roadmaps and prioritize data science efforts based on business value, feasibility, risk, and team capacity.
• We mentor data scientists and ML practitioners through design reviews, code reviews, modeling best practices, and knowledge sharing.
• We work with ML engineering to productionize models and GenAI services using AWS-native tools and modern MLOps practices.
• We contribute to scalable ML system design, including data pipelines, feature workflows, model serving, observability, monitoring, and lifecycle management.
• We apply strong software engineering practices such as version control, CI/CD, testing, reproducibility, containerization, and documentation.
• We support deployment patterns for both batch and low-latency inference use cases.
• We partner with security, governance, architecture, and legal/privacy stakeholders to ensure AI systems are reliable, secure, compliant, and responsibly deployed.
• We collaborate with product owners, data scientists, ML engineers, data engineers, architects, and business stakeholders to deliver end-to-end algorithmic products.
• We communicate model behavior, limitations, assumptions, risks, and business impact clearly to technical and non-technical audiences.
• We define measurable success criteria and evaluate whether AI solutions are achieving the intended outcomes.
• We champion responsible AI, inclusive design, and practical experimentation across projects.

• AI
• AWS
• Lambda
• CI/CD
• Cloud
• Docker
• Fine-tuning
• Support
• LLM
• Machine Learning
• MLOps
• Model Serving
• Python
• PySpark
• SQL
• Security

More:

We are Hyatt Hotels Corporation, a hospitality company built on a culture of care, belonging, empathy, inclusion, integrity, experimentation, respect, and wellbeing. Since 1957, our colleagues and guests have shaped our growth into one of the worlds best and fastest-growing hospitality brands. We are expanding rapidly and offer exciting opportunities for career development and upward mobility. This Lead Data Scientist role sits within our AIML team and focuses on search, personalization, and agents, working closely with ML Engineering, Data Engineering, Platform, Product, and Finance. We offer a flexible work schedule, annual free hotel stays at Hyatt hotels globally, wellbeing support including a complimentary Headspace subscription and fitness center discount, family assistance benefits, and paid time off, medical, dental, vision, and 401K with company match. The salary range for this position is $180,000 to $210,000, and the role is also eligible for an annual bonus.

last updated 33 week of 2026

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