Beca AI Engineer (incorporación mayo 2026)
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About the Role
Who We Are
VML, part of WPP, is a leading creative company that combines brand experience, customer experience, and commerce, creating connected brands to drive growth. VML is celebrated for its innovative and human first, award-winning work for blue chip client partners including AstraZeneca, Colgate-Palmolive, Dell, Ford, Microsoft, Nestlé, The Coca-Cola Company, and Wendy's. The agency is recognized by the Forrester Wave™ Reports, as a Leader among Marketing Creative and Content Service Providers, Commerce Services, Global Digital Experience Services, Global Marketing Services and, most recently, Marketing Measurement & Optimization. In addition, VML’s specialist health network, VML Health, is one of the world’s largest and most awarded health agencies. VML’s global network is powered by 26,000 talented people across 55+ markets, with principal offices in Kansas City, New York, Detroit, London, São Paulo, Shanghai, Singapore, and Sydney.
About WPP
WPP is the trusted growth partner for the world’s leading brands. We unite cutting-edge media intelligence and data solutions, world-class creativity, next-generation production, transformative enterprise solutions and expert strategic counsel in a single company – powered by exceptional talent and our agentic marketing platform, WPP Open, to help our clients navigate change, capture opportunity and deliver transformational growth. For more information, visit WPP.com.
¿Quieres ser parte de este crecimiento? Esto es lo que buscamos:
La beca de AI Engineer está orientada a personas que quieran desarrollarse en el diseño, implementación y mejora de soluciones basadas en inteligencia artificial. Durante el programa, la persona seleccionada colaborará con el equipo en proyectos reales, participando en la experimentación, desarrollo e integración de modelos de IA y herramientas asociadas, siempre con acompañamiento técnico y oportunidades de aprendizaje continuo.
Día a día de la beca
Apoyarás en la:
- Investigación y análisis de casos de uso para aplicar inteligencia artificial.
- Desarrollo, prueba y mejora de modelos y/o pipelines de IA.
- Preparación, limpieza y análisis de datos para entrenar o evaluar modelos.
- Integración de soluciones de IA en productos, procesos o herramientas internas.
- Documentación técnica y seguimiento de experimentos y resultados.
- Participación en reuniones con el equipo para revisar avances, retos y próximos pasos.
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