Machine Learning Engineer Especialista II (Diretoria de Dados - Consumidor)
Tasks
- Build end-to-end machine learning pipelines
- Build generative AI data pipelines for unstructured to structured data
- Collaborate with cross functional teams on machine learning use cases
- Create pilots and prototypes with business teams
- Design and implement cloud architectures for AI and data
- Develop automated model training and prediction workflows
- Document processes APIs technical decisions and postmortems
- Maintain MLOps development deployment and maintenance best practices
- Monitor model quality efficiency cost and usage
Perks/Benefits
- Birthday day off
- Dental insurance
- Educational support programs
- Fitness and wellness partnerships
- Fully remote work
- Home office support
- Life insurance
- Meal allowance
- Medical insurance
- Private pension plan
- Telemedicine
- Transportation assistance
- Wellness initiatives
Skills/Tech-stack
API documentation | Airflow | Amazon Web Services | Apache Beam | Apache Spark | Cloud Architecture | Cloud platform | Containers | Data Pipelines | Data Processing | Distributed data | Distributed data processing | Docker | Generative AI | Google Cloud | Google Cloud Platform | Kubeflow | MLOps | Machine Learning | Microsoft Azure | Model Deployment | Model Monitoring | OWASP | Python | Recommendation Systems | SQL | Supervised Learning | Unsupervised Learning | Vertex AI | Web Services
Education
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