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I am a MLOps Engineering Architect working within Machine Learning Projects since 2018, my main goal is to contribute to MLOps CI/CD/CT development processes that improve Advanced Analytics Teams technical debt and help the business grow shortening market delivery time with ML Solutions.

I’ve been working alongside several and diverse teams for more than 10 years driving scalable developments projects. This path allowed me to acquire business understandment, teams leadership and technical skills.

Python - Docker - Hadoop - Hive - Spark - Airflow - Pandas - Git - AWS - GCP - Oracle DB - MongoDB - Presto - MySQL - AWS Sagemaker - AWS CloudFormation - GCP Vertex AI - Kubeflow - Fast API - GitHub Actions - Terraform - Databricks

• 🔭 I’m currently working as MLOps Engineer Contractor, Architecting and Developing E2E MLOps Solutions in cloud AWS and GCP Services.
• 🌱 I’m currently learning Cloud Machine Learning Ops, CI/CD/CT strategies, ML scalable solution architectures.
• 👯 I’m looking to collaborate on ML & Big Data Projects.
• 🤔 I’m looking for help with solutions that challenge the approach to build scalable ML Projects.
• 💬 Ask me about Spark Hadoop Hive Hdfs on premise solutions. AWS and GCP ML Solutions arquitectures.
• 📫 How to reach me: [email protected]