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Xideral

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MLOps Engineer – Systems, DevOps, MLOps, Cybersecurity

DevOps EngineerDevOps EngineerFull TimeRemoteSeniorTeam 201-500Since 2004H1B No SponsorCompany SiteLinkedIn

Location

Mexico

Posted

137 days ago

Salary

0

Seniority

Senior

Bachelor Degree5 yrs expSpanishEnglishKubernetesPython

Job Description

MLOps Engineer – Systems, DevOps, MLOps, Cybersecurity

Xideral

• Construir, desplegar y mantener pipelines de ML en modelos de machine learning listos para producción • Procesar enormes flujos de datos para flujos de trabajo de ML escalables • Definir y desarrollar APIs y servidores MCP para apoyar soluciones de ML • Trabajar en colaboración con Científicos de Datos, Ingenieros de Datos, y ML Engineers para coordinar pipelines, mantenimiento y entrenamiento en producción • Procesar y gestionar conjuntos de datos estructurados y no estructurados a gran escala • Aplicar conocimiento empresarial para analizar datos, generar insights y resolver problemas complejos • Realizar análisis de datos ad-hoc basado en necesidades empresariales • Participar en el análisis de problemas y resolución relacionados con el flujo y contenido de datos con partes interesadas • Establecer relaciones sólidas con clientes y equipos internos, asegurando alta satisfacción del cliente • Promover mejores prácticas, innovación y mejora continua en los procesos de MLOps

Job Requirements

  • 5+ años de experiencia como MLOps Engineer, con experiencia desarrollando pipelines CI/CD en Producción
  • Experiencia con herramientas de ciclo de vida de ML como MLflow y Kubeflow
  • Experiencia práctica usando Weights & Biases para seguimiento de experimentos
  • Experiencia práctica usando Databricks para flujos de datos y ML escalables
  • Habilidades avanzadas en programación en Python
  • Experiencia práctica con Kubernetes para orquestación de contenedores
  • Sólido entendimiento de flujos de trabajo de entrenamiento e inferencia de ML
  • Experiencia en preparación de datos y ingeniería de características
  • Familiaridad con estrategias de implementación de ML en el Edge

Benefits

  • Salary Atractivo + Beneficios Premium
  • Bonos por desempeño
  • Cupones de supermercado y ahorros
  • Aguinaldo, vacaciones premium, y vacaciones pagadas
  • SGMM Seguro médico, familiar y de vida

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