AI Engineer developing cutting - edge AI models and frameworks in a hybrid setup at a tech startup. Collaborating closely with founders to shape the future of AI technology.
About the role
- Machine Learning Engineer developing impactful ML models at Stefanini. Collaborating with cross-disciplinary teams in a hybrid work setup maximizing business solutions.
Responsibilities
- Participar con equipos multidisciplinarios para desarrollar soluciones de machine learning end-to-end
- Transformar necesidades de negocio en modelos de ML que generen impacto en el negocio
- Diseñar, desarrollar y desplegar pipelines de modelos de ML escalables en entornos de producción
- Diseñar, desarrollar y desplegar APIs para servir modelos de ML integrados con procesos empresariales
- Implementar pipelines CI/CD con testing automatizado, gates de calidad e Infraestructura como código
- Implementar observabilidad integral con monitoreo de data drift y model drift para el seguimiento del performance de modelo
Requirements
- Titulado/Bachiller en Ingeniería de Software, Ciencias de la Computación, Ingeniería de Sistemas, Estadística o afines. Con especializaciones en MLOps
- +3 años de experiencia en desarrollo e implementación de modelos de ML en producción
- Dominio AWS (Lamda, API Gateway, VPC, IAM)
- Dominio GCP (Cloud Fuction, Dataflow, Cloud Run, Cloud Composer, Vertex, CloudLogging)
- Dominio GCP para ML (Vertex Feature Store, Vertex Pipeline, Vertex Endpoint , Vertex Model Monitoring )
- Experiencia en frameworks para pipelines ML (Kedro, Kubeflow, Apache Airflow) y Big Data (PySpark, Apache Beam)
- Experiencia en frameworks para APIs (FastAPI, Django) y bases de datos (Bigquery, BigTable, CloudSQL, FireStore),
- Experiencia en CI/CD para ML, Git , containerización (Docker, Kubernetes), IaC (Terraform), Azure DevOps
Benefits
- Trabajo híbrido
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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