Senior Manager, Gen AI (Hybrid opportunity)

Salary Details

Salary Description: Competetive Salary Offered

Job Description For Senior Manager, Gen AI (Hybrid opportunity)

Description

The Opportunity

Hyatt Hotels Corporation seeks an enthusiastic Gen AI Engineering leader to help build the algorithmic assets and features that Hyatt guests, members, customers, and internal users leverage to transform the guest experience and drive efficiencies across the operations of our business.

In this role, you will design and implement Gen AI solutions and partner closely with ML Engineering, Personalization, Forecasting, and Decision Science domains. This role will work cross-functionally with various data science teams, data engineering teams, and data architecture teams. The ideal candidate can be a hands-on technical leader who is skilled as an implementation engineer while also leading the team to innovate and build cutting-edge Gen AI products and services.

You will be a part of a ground-floor, hands-on, highly visible team which is positioned for growth and is highly collaborative and passionate about machine learning and AI.

Applying the latest techniques and approaches across the domains of data science, machine learning, and AI isn't just a nice to have, it's a must. You will be part of a team passionate about diversity, equity, and inclusion, committed to nurturing curiosity and new skills and building connections with stakeholders, colleagues, and guests across the organization.

Who We Are

At Hyatt, we believe in the power of belonging and cultivating a culture of care where our colleague's become family. Since 1957, our colleagues and our guests have served as the heart of our business and made Hyatt one of the best hospitality brands in the world, with more than 1,500 hotel, all-inclusive, and wellness resort properties in 70 countries across six continents.

We turn trips into journeys, encounters into experiences and jobs into careers. As we continue to grow-we never lose sight of what's most important: People.

Why Now?

We are in a time of extraordinary transformation. Passion for personal travel combined with the explosive growth of global business has underpinned our growth for years. Hyatt is at the epicenter of the evolution of travel-and we are looking for passionate changemakers to be a part of our journey. At the heart of Hyatt is our shared belief that hospitality is more than just a job-it's a career for people that care.

How We Care for Our People

Wellbeing is the ultimate realization of our purpose - we care for people so they can be their best. We believe this focus on our colleagues is the key to our success and we've earned a place on Fortune's prestigious "100 Best Companies to Work For®" for the last nine years.

We're proud to offer exceptional corporate benefits which include:

• Paid Time Off, Medical, and other benefits.
• Annual allotment of free hotel stays at Hyatt hotels globally.
• Flexible work schedule.

Who You Are

You are a seasoned and passionate technical leader with a demonstrable experience in leading and mentoring engineering teams, delivering enterprise-grade AI/ML platforms and products with a strong focus on Gen AI capabilities. You thrive in dynamic environments and value experimentation, empathy, and business alignment.

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The Role

Leadership & People Management

• Provide overall leadership for the Mexico City office, ensuring alignment with company strategy, culture and business objectives.
• Oversee daily operations of the site and serving as the primary point of contact for all site related matters, including facilities, safety and operational performance.
• Build and maintain strong relationships with local teams, fostering collaboration across teams and with global stakeholders.
• Partner with HR, IT and other enabling functions to ensure smooth onboarding, support, and development for colleagues based in Mexico City.
• Lead, mentor, and develop a team of ML engineers; foster a high-performing, psychologically safe, and inclusive team culture.
• Drive hiring, performance management, career growth, and technical upskilling across the team.
• Translate Hyatt's ML strategy into actionable team roadmaps and deliverables.
• Act as a thought partner to Product and Data Science leadership; provide strong technical and organizational guidance.

Qualifications
Experience Required:

• Master's degree in computer science, Software Engineering, or related field. Ph.D preferred.
  
• 6+ years of experience in machine learning roles focused on areas such as NLP/NLU, reinforcement learning or LLM applications, including 3+ years of people management experience in a tech leadership role.
  
• Experience in fine-tuning and deploying LLMs or other Generative AI solutions to production.
  
• Expertise in AWS cloud services (e.g., SageMaker, ECS/EKS, Step Functions, Lambda, Glue).
  
• Strong programming skills in Python, with experience in SQL, PySpark, and containerization (e.g., Docker).
  
• Proven experience designing scalable data pipelines and ML systems for both real-time and batch inference.
  
• Deep understanding of responsible AI practices, CI-CD pipelines, Agile development practices, and model lifecycle management.
  
• Excellent interpersonal and communication skills, with a strong bias for action and collaboration.
  
• Familiarity with ML observability and governance tools.
  
  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.
  

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Reality Check:

Research shows that women, people of color and others who belong to historically - excluded groups tend to apply to jobs, only if they met all of the 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.

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.