Metova, Inc. logo
Metova, Inc.

Helping companies transform their business through technology to meet the growing expectations of their customers.

Technical Leader (Conversational AI)

Technical Product ManagerTechnical Product ManagerFull TimeRemoteMid LevelTeam 201-500Since 2006H1B No SponsorCompany SiteLinkedIn

Location

Mexico

Posted

2 days ago

Salary

0

Seniority

Mid Level

No structured requirement data.

Job Description

Technical Leader (Conversational AI)

Metova, Inc.

Role Description Buscamos un(a) Líder Técnico con experiencia en el desarrollo y liderazgo de soluciones de datos e inteligencia artificial. Este rol combina habilidades técnicas avanzadas con liderazgo estratégico para guiar equipos en la creación de productos innovadores que aprovechen el poder de los datos y la IA. El candidato ideal será responsable de definir la arquitectura técnica, supervisar la implementación de soluciones y garantizar la alineación con los objetivos del negocio. - Definir, supervisar y diseñar la arquitectura técnica de soluciones basadas en datos e inteligencia artificial, estableciendo la visión tecnológica y seleccionando herramientas y frameworks adecuados. - Liderar equipos multidisciplinarios en el diseño, desarrollo y operación de soluciones de machine learning, IA generativa y procesamiento de lenguaje natural, incluyendo microservicios y arquitecturas orientadas a eventos. - Validar con el equipo de MLOps, el ciclo de vida de los modelos: entrenamiento, validación, despliegue con CI/CD, monitoreo y retraining. - Desplegar e integrar chatbots en WhatsApp, incluyendo el conocimiento del modelo de precios por mensaje, la categorización (marketing, autenticación, utilidad) y la integración fluida con agentes humanos para escalamiento y resolución. - Colaborar activamente con áreas de producto, negocio y UX, traduciendo requerimientos estratégicos en soluciones técnicas escalables y sostenibles. - Asegurar calidad técnica, promoviendo buenas prácticas de desarrollo, revisiones de código, definición de estándares y métricas de desempeño. - Explorar y adoptar nuevas tecnologías en IA (modelos supervisados/no supervisados, detección de anomalías, grafos, generative AI), manteniéndose actualizado en tendencias y mejores prácticas. - Garantizar la gobernanza y seguridad de datos, cumpliendo con políticas de privacidad, control de acceso y cumplimiento regulatorio. Qualifications - Experiencia comprobable (5+ años) liderando proyectos de IA, ciencia de datos o analítica avanzada, incluyendo al menos 2 años con LLMs o IA generativa. - Experiencia en diseño e implementación de soluciones de detección de anomalías y patrones de comportamiento, especialmente en contextos de riesgo o fraude. - Sólido conocimiento en machine learning supervisado y no supervisado (regresión, árboles, clustering, SVM, boosting, etc.). - Dominio de Python y frameworks de machine learning como Scikit-Learn, PyTorch y TensorFlow. - Experiencia en arquitectura backend, diseño de microservicios, APIs REST, bases de datos relacionales (PostgreSQL, SQL Server) y NoSQL (MongoDB, Neo4J, etc.), y mensajería asíncrona (Kafka, RabbitMQ, etc.). - Conocimiento del ecosistema WhatsApp Business: API oficial, categorías de mensaje, modelo de precios y estrategias de optimización de costos. - Experiencia diseñando e implementando microservicios y arquitecturas orientadas a eventos. - Conocimiento en Docker, Kubernetes, CI/CD, sistemas de monitoreo, pipelines de entrenamiento y despliegue continuo. - Sólido entendimiento de técnicas de NLP, detección de anomalías y teoría de grafos, con aplicación práctica en soluciones empresariales. - Enfoque hands-on, con capacidad de liderar técnicamente y participar activamente en codificación, revisión de modelos y definición de arquitecturas. Requirements - Experiencia implementando soluciones multicloud en Azure, AWS y (deseable) GCP. - Implementación de gobierno de datos y seguridad de datos. - Implementación de pipelines de ML/IA en producción, incluyendo monitoreo y retraining automatizado. - Conocimiento en diversos lenguajes de programación como C# (.NET), Java, Golang. - Implementación de modelos de Monetización de datos. - Conocimiento en teoría de grafos aplicada a detección de comunidades, relaciones entre entidades y análisis de redes complejas.

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