20 publicaciones de empleo destacadas de ai model optimization software en ciudad de méxico, dif (¡Están contratando!)

Senior Machine Learning Engineer (Remote opportunity)
Hyatt Corporate Office —Ciudad de México, CDMX
- Tiempo completo
- Home Office (Desde casa)
- Informática
- Maestría
- Vacaciones adicionales o permisos con goce de sueldo
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Boston Consulting Group —Ciudad de México
- Tiempo completo
- CRM software
- Oracle
- Administración de personal
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Edenred —Ciudad de México, CDMX
- Tiempo completo
- Azure
- Administración de personal
- Informática
BCG Platinion | AI Tech Consultant, Enterprise Solutions
Boston Consulting Group —Ciudad de México
- Tiempo completo
- CRM software
- Oracle
- Administración de personal
Senior Software Engineer (Python + Distributed systems)
Scribd, Inc. —Ciudad de México, CDMX
- Tiempo completo
- Informática
- CAD
- Licenciatura
- Seguro dental
- Vacaciones adicionales o permisos con goce de sueldo
Partner Specialist Intern (US & Canada Market)
Deliverect —Ciudad de México, CDMX
- Tiempo completo
- Trabajo híbrido
- Inglés
- Licenciatura
Postulación rápida
Senior Backend Engineer (Python) - Content Understanding
Scribd, Inc. —Ciudad de México, CDMX
- Tiempo completo
- Informática
- CAD
- Licenciatura
- Seguro dental
- Vacaciones adicionales o permisos con goce de sueldo
Professional, Technology Project Management
BSA-JLL - LaSalle Partners, MEX —Ciudad de México, CDMX
- Tiempo completo
- Microsoft Excel
- Administración de personal
- PMP
Postulación rápida
Transformation Delivery Consultant
Thomson Reuters —Ciudad de México, CDMX
- Tiempo completo
- Administración de personal
- Licenciatura
- Sin título de educación superior
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Requirements Engineer III, Mexico City (MX)
Swiss Re —Ciudad de México, CDMX
- Azure
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Data Scientist , Amazon Music - DISCO
Servicios Comerciales Amazon Mexico S. de R.L. de C.V. —Ciudad de México, CDMX
- Tiempo completo
- Doctorado
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Delinea —Ciudad de México, CDMX
- Tiempo completo
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Imubit —Ciudad de México, CDMX
- Home Office (Desde casa)
- Administración de personal
- Licenciatura
- Mejora continua
Marketing Manager - Reuters Events
Thomson Reuters —Ciudad de México, CDMX
- Tiempo completo
- Administración de personal
- Salesforce
Research Engineering Automation
Teradata —Ciudad de México, CDMX
- Tiempo completo
- Informática
- Maestría
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Finance Director (Strategic Finance Lead)
Devsu —Ciudad de México, CDMX
- Tiempo completo
- Home Office (Desde casa)
- Microsoft Excel
- Maestría
- Licenciatura
Postulación rápida
11d
Senior Data Engineer
NielsenIQ —Ciudad de México, CDMX
- $55,000 a $70,000 por mes
- Tiempo completo
- Trabajo híbrido
- Azure
- DevOps
- Inglés
Postulación rápida
Partner Sales Manager, Startups
Amazon Web Services Mexico S. de R.L. de C.V. —Ciudad de México, CDMX
- Tiempo completo
- Experiencia en ventas
- Inglés
- Licenciatura
Sr Governance and Compliance Analyst
Thomson Reuters —Ciudad de México, CDMX
- Tiempo completo
- Azure
- Inglés
- Licenciatura
Marketing Cloud Success Architect
Salesforce —Ciudad de México, CDMX
- Tiempo completo
- Administración de personal
- Salesforce
- DevOps
- Permiso de maternidad y paternidad

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Senior Machine Learning Engineer (Remote opportunity)

Hyatt Corporate Office -
Ciudad de México, CDMX

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Información del empleo

Tiempo completo

Beneficios

Vacaciones adicionales o permisos con goce de sueldo

Cualificaciones

Informática
Ingeniería de software
Maestría
Seguridad

Descripción completa del empleo

Summary

The Opportunity

Hyatt Hotels Corporation seeks an enthusiastic Senior ML Engineer to join our Data Science and Machine Learning department. In this role, you will be collaborating closely with the broader Data and Analytics 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.

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 to 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 for the last ten years. 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
Paid Time Off, Medical.

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 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 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

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.

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.

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