Summary: The Opportunity Hyatt Hotels Corporation seeks an enthusiastic Sr. AI/ML Engineer to join our Data and Analytics department. In this role, you will be collaborating closely with the broader Machine Learning and AI 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.
Who We Are At Hyatt, we believe in the power of belonging and creating a culture of care, where our colleagues become family. Since 1957, our colleagues and our guests have been at the heart of our business and helped Hyatt become one of the best and fastest-growing hospitality brands in the world. Our transformative growth and the addition of new hotels, brands, and business lines can open the door for exciting career and growth opportunities for our colleagues.
As we continue to grow, we never lose sight of what's most important: People. We turn trips into journeys, encounters into experiences, and jobs into careers.
Why Now? This is an exciting time to be at Hyatt. We are growing rapidly and are looking for passionate changemakers to be a part of our journey. The hospitality industry is resilient and continues to offer dynamic opportunities for upward mobility, and Hyatt is no exception.
How We Care for Our People What sets us apart is our purpose-to care for people so they can be their best. Every business decision is made through the lens of our purpose, and it informs how we have and will continue to support each other as members of the Hyatt family. Our care for our colleagues is the key to our success. We're proud to have earned a place on Fortune's prestigious 100 Best Companies to Work For list since 2013. This recognition is a testament to the tremendous way our Hyatt family continues to come together to care for one another, our commitment to a culture of inclusivity, empathy, and respect, and making sure everyone feels like they belong.
We're proud to offer exceptional corporate benefits which include:
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, 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
Who You Are As our ideal candidate, you understand the power and purpose of our culture of care, and embody our core values of Empathy, Inclusion, Integrity, Experimentation, Respect, and Wellbeing. You enjoy working with others, are results-driven, and are looking for a variety of opportunities to develop personally and professionally.
The Role The Senior AI/ML Engineer builds and operates the shared platforms that AI product engineering teams use to develop and run AI applications, agents, and models. This is a hands-on role focused on reliable, reusable, self-service capabilities that cut duplicated effort and shorten the path from experimentation to production, with internal engineering teams as the customers.
The role delivers scalable AI/ML platforms, including runtimes, orchestration, tool and enterprise system integration, evaluation, and observability, and the real-time serving systems delivered as APIs: supporting products including recommendation engines, information retrieval and search, and other ML and AI backends. Shared services include inference, model deployment pipelines, feature stores, and embedding and vector search services, covering the model and agent lifecycle from versioning through deployment and monitoring. System design is central: defining service boundaries, APIs, and data flows, and making sound tradeoffs across scalability, latency, reliability, security, and cost.
The engineer contributes directly to architecture, Python development, code reviews, and production problem solving across AWS and Google Cloud Platform, partnering with product engineering, data, infrastructure, and security teams. Success is measured by adoption and reliability of the platform and by how consistently product teams ship to production.
Qualifications: Experience Required: - 7+ years of software engineering experience in cloud-based environments, with a focus on AI engineering, machine learning engineering, platform engineering, or distributed systems, including hands-on ownership of production services.
- Demonstrated experience designing, developing, deploying, and operating shared platforms, reusable services, or developer tools consumed by multiple engineering or data science teams.
- Strong experience with end-to-end system design, including translating technical requirements into architectures, APIs, service interfaces, integration patterns, and production implementations.
- Experience building and operating production AI or machine learning systems, including agent-based applications, model serving, deployment, evaluation, monitoring, or enterprise integrations.
- Experience working independently on complex technical problems, making engineering tradeoffs, and taking accountability for services from initial design through production operations and ongoing improvements.
- Experience collaborating across engineering, data, infrastructure, security, and product teams to deliver scalable and reliable technical solutions.
- Master's degree in Computer Science, Engineering, Mathematics, Physics, or a related technical discipline, or equivalent practical experience
- Strong system design skills, including distributed systems, service boundaries, APIs, design patterns, data flows, and engineering tradeoffs across reliability, performance, scalability, security, and cost.
- Strong Python development skills, including experience building production services, reusable libraries, APIs, SDKs, and developer tools.
- Experience developing AI agent systems using agent runtimes, orchestration frameworks, tool integrations, memory and context management, retrieval, evaluation, guardrails, and observability.
- Experience with shared AI infrastructure, including real-time and batch inference services, embedding services, vector databases, model deployment pipelines, and feature stores.
- Solid understanding of machine learning fundamentals and lifecycle capabilities, including model training and serving, registration, versioning, validation, evaluation, deployment, monitoring, and explainability.
- Experience with AWS and Google Cloud Platform, including strong hands-on production expertise in at least one. Familiarity with managed AI and machine learning services such as Vertex AI, Gemini, or equivalent technologies.
- Experience with Docker, container orchestration, infrastructure as code, automated testing, and CI/CD practices for building and operating production services.
- Experience with SQL and batch or streaming data processing architectures. Familiarity with PySpark, streaming ingestion, online feature serving, or distributed data processing preferred.
- Experience with service and AI observability, including logging, metrics, distributed tracing, and agent or LLM evaluation tools such as Datadog, Arize, or equivalent technologies.
- Familiarity with agent interoperability and tool integration protocols such as Model Context Protocol (MCP), Agent-to-Agent (A2A), or equivalent frameworks preferred.
- Experience with recommender systems, ranking systems, forecasting, experimentation platforms, or real-time decisioning systems preferred.
The position responsibilities outlined above are in no way to be construed as all-encompassing. Other duties, responsibilities, and qualifications may be required and/or assigned as necessary.
We welcome you: Research shows that individuals tend to apply to jobs only if they meet all the listed job qualifications. Unsure if you check every box, but feeling inspired to enhance your career? Apply. We'd love to consider your unique experiences and how you could make Hyatt even better.
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.
We value our relationships with recruitment partners and require that agencies contact us first before submitting any candidates. Hyatt will not be responsible for any fees and obligations associated with unsolicited submissions unless a formal agreement is in place.
