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Urgent! Ingeniero(a) Machine Learning Job Opening In Santiago – Now Hiring Innomotics

Ingeniero(a) Machine Learning



Job description

Overview


Buscamos Ingeniero(a) Machine Learning para unirse a nuestro equipo en Innomotics.


Ubicación: Santiago de Chile, CL, .



Responsibilities



  • Participar en el diseño, desarrollo e integración de aplicaciones, incorporando funcionalidades impulsadas por IA/ML y modelos de lenguaje (LLMs).


  • Impulsar la adopción de nuevas tecnologías asociadas a IA generativa, servicios cloud (Azure OpenAI, AWS Bedrock, MCP) e integraciones que generen valor para el negocio digital.


  • Responsable del ciclo de vida de modelos ML y aplicaciones de IA (diseño, entrenamiento, fine-tuning, implementación, monitoreo y reentrenamiento automático).


  • Desarrollar y mantener pipelines y CI/CD para despliegue automatizado de modelos y código, incluyendo versionado.


  • Liderar buenas prácticas en desarrollo ML/AI y coaching a otros miembros del equipo.


  • Participar en el modelamiento, preparación y features para entrenamiento de modelos, aplicando técnicas de ETL, feature stores y optimización de datos.


  • Desarrollar pruebas de concepto con LLMs, sistemas RAG y MVP de IA que validen casos de uso de negocio en plazos acotados.


  • Administrar y optimizar recursos cloud para ML (Docker, APIs), asegurando eficiencia de costos y rendimiento.


  • Implementar sistemas de monitoreo de modelos, detección de drift y alertas de performance en producción.


  • Mantener actualizada la documentación técnica de modelos, experimentos y arquitecturas ML en repositorios colaborativos.


  • Colaborar con product managers y stakeholders para traducir requerimientos de negocio en soluciones técnicas de IA escalables.


  • Brindar soporte técnico en demos de IA y presentaciones a clientes cuando sea requerido.




Tu perfil



  • Formación profesional en Ciencias de la Ingeniería, tales como Electricidad, Informática, Matemáticas, Estadística, Mecánica, Ingeniería de Datos o carrera afín.


  • Contar con al menos 4-6 años de experiencia en Machine Learning Engineering con enfoque en producción (Excluyente).


  • Fundamentos ML/Estadística: Sólida formación en estadística aplicada, modelado predictivo (supervisado/no supervisado), series de tiempo, y análisis de datos estructurados/no estructurados.


  • Python Avanzado (Excluyente): Pandas, NumPy, Scikit-learn, Statsmodels para análisis estadístico y preparación de datos.


  • Deep Learning y LLMs: PyTorch/TensorFlow, Transformers, experiencia práctica con fine-tuning de LLMs y sistemas RAG.


  • Desarrollo y Producción: Django/Flask para APIs ML, LangChain para aplicaciones LLM, desarrollo de agentes inteligentes y sistemas conversacionales.


  • Bases de Datos: SQL avanzado (PostgreSQL), experiencia con TimescaleDB o Influx para series de tiempo, vector databases para embeddings.


  • MLOps y Despliegue: Git, Azure DevOps/AWS CodePipeline, CI/CD para modelos ML, Docker, containerización de modelos.


  • Cloud ML: Azure ML/AWS SageMaker, servicios de IA cloud, deployment escalable, optimización de costos.


  • Visualización y Análisis: Tableau/Power BI para reportería de negocio.


  • Ingles conversacional.




Deseables



  • NLP avanzado, experiencia en áreas de minería/industrial, conocimientos de protocolos industriales como OPC, Automatización APC, etc.




¿Te animas a impulsar el futuro con nosotros?

Únete a Innomotics y comienza a hacer la diferencia ahora.

#TeamInnomotics #JoinReliableMotion



Innomotics es un empleador que ofrece igualdad de oportunidades y valora la diversidad.

No discrimina por motivos de raza, religión, color, nacionalidad, género, orientación sexual, edad, estado civil o discapacidad.



Jobs at Innomotics


Descubre más sobre trabajos y carreras en Innomotics.



Seniority level



  • Mid-Senior level



Employment type



  • Full-time



Job function



  • Engineering and Information Technology



Industries



  • Machinery Manufacturing

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Required Skill Profession

Desarrollo De Software



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