Senior DevOps y MLOps Freelance

hace 1 mes


Barcelona, Barcelona, España Sapientis A tiempo completo

Descripción del Puesto

Estamos buscando un profesional con amplia experiencia en la gestión de infraestructuras y operaciones de machine learning en entornos de nube como Azure y AWS. El candidato ideal será responsable de diseñar, implementar y mantener sistemas que aseguren el despliegue continuo y la eficiencia operacional de nuestros modelos de inteligencia artificial.

Responsabilidades

  • Diseñar y gestionar infraestructuras en la nube (Azure y AWS) para soportar operaciones de DevOps y MLOps.
  • Implementar y mantener pipelines de CI/CD para el despliegue de aplicaciones y modelos de machine learning.
  • Colaborar con los equipos de desarrollo y ciencia de datos para asegurar la integración continua y la entrega eficiente de software y modelos.
  • Automatizar procesos de despliegue y monitoreo para asegurar la disponibilidad y escalabilidad de los sistemas.
  • Implementar soluciones de seguridad y gobernanza en los entornos de nube.
  • Optimizar el uso de recursos en la nube para maximizar el rendimiento y minimizar costos.
  • Resolver problemas de infraestructura y realizar mantenimiento preventivo.

Requisitos

  • Experiencia Profesional: Mínimo 5 años de experiencia en DevOps y MLOps.
  • Nube: Experiencia demostrable con Azure y AWS.
  • CI/CD: Conocimiento profundo de herramientas de integración y entrega continua.
  • Infraestructura como Código: Experiencia con Terraform, Ansible, o similares.
  • Automatización: Habilidad para escribir scripts y automatizar procesos utilizando Python, Bash, o similares.
  • Seguridad en la Nube: Conocimiento en implementación de políticas de seguridad y mejores prácticas.
  • Monitoreo y Logging: Experiencia con herramientas de monitoreo y logging (Prometheus, Grafana, ELK Stack, etc.).
  • Comunicación: Excelentes habilidades de comunicación y colaboración en entornos remotos.

Requisitos Deseados

  • Certificaciones en Azure y/o AWS.
  • Experiencia con contenedores y orquestación (Docker, Kubernetes).
  • Familiaridad con plataformas de MLOps como MLflow, Kubeflow, o similares.
  • Experiencia en la optimización de recursos y costos en la nube.
  • Conocimientos en metodologías ágiles y gestión de proyectos.

Puedes enviar tu cv a ******, indicando la referencia de la posición

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