MLOps
On-siteBuenos Aires, Buenos Aires F.D., Argentina
Job Summary
Manage the full lifecycle of Machine Learning and AI models and applications from deployment to production operations. Implement secure deployment strategies using containers and automation tools while administering cloud and on-premise development, testing, and production environments. Provide Level 2 support for AI applications by analyzing incidents and ensuring operational continuity through monitoring, alerting, and observability on model performance, data drift, and quality. Design CI/CD pipelines for ML and manage model, dataset, and artifact versioning to guarantee traceability and reproducibility. Uphold security, compliance, and access management within the AI ecosystem while collaborating with Data Science, Engineering, and Product teams.
Required Qualifications
- Experiencia de al menos 3 años en posiciones de MLOps, DevOps orientado a Machine Learning o DataOps
- Dominio de Python y Bash
- Experiencia trabajando con contenedores (Docker) y herramientas de automatización e integración continua (GitHub Actions, GitLab CI/CD, Jenkins o similares)
- Conocimientos sólidos de infraestructura Cloud (AWS, GCP o equivalentes)
- Experiencia con herramientas de monitoreo y observabilidad como Grafana, Datadog, Prometheus o similares
- Experiencia utilizando herramientas de gobierno y versionado de modelos como MLflow, DVC, Vertex AI o equivalentes
- Conocimientos de Terraform o herramientas de Infrastructure as Code
- Manejo de Git y Jira (o herramientas similares)
Desired Qualifications
- Experiencia participando en proyectos de Inteligencia Artificial Generativa
- Conocimientos de Kubernetes, Helm o herramientas de orquestación
- Experiencia con frameworks de GenAI como LangChain, Hugging Face o similares
- Conocimientos de herramientas como Kubeflow, SageMaker, Vertex AI, Feast, Airflow, Prefect o equivalentes
- Experiencia construyendo agentes de IA
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