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Hi, I’m Juan Sebastian Camargo Barragan, a machine learning engineer focused on building scalable ML pipelines, cloud-native infrastructure, and end-to-end AI solutions. I specialize in MLOps, Kubernetes, Kubeflow, MLflow, and automation across data ingestion, model training, experiment tracking, and deployment to accelerate AI initiatives. Currently based in Barcelona, I work on end-to-end ML automation at I2CAT Foundation, delivering distributed ML pipelines for 5G/IoT and scalable AI services. I enjoy collaborating with research and engineering teams across research-to-production cycles, turning complex problems into robust, scalable systems and continuously improving deployment and performance of ML solutions.…Hi, I’m Juan Sebastian Camargo Barragan, a machine learning engineer focused on building scalable ML pipelines, cloud-native infrastructure, and end-to-end AI solutions. I specialize in MLOps, Kubernetes, Kubeflow, MLflow, and automation across data ingestion, model training, experiment tracking, and deployment to accelerate AI initiatives. Currently based in Barcelona, I work on end-to-end ML automation at I2CAT Foundation, delivering distributed ML pipelines for 5G/IoT and scalable AI services. I enjoy collaborating with research and engineering teams across research-to-production cycles, turning complex problems into robust, scalable systems and continuously improving deployment and performance of ML solutions.

Juan Sebastian Camargo Barragan

Data Scientist, AI Engineer, Cloud Developer, +2

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Hi, I’m Juan Sebastian Camargo Barragan, a machine learning engineer focused on building scalable ML pipelines, cloud-native infrastructure, and end-to-end AI solutions. I specialize in MLOps, Kubernetes, Kubeflow, MLflow, and automation across data ingestion, model training, experiment tracking, and deployment to accelerate AI initiatives. Currently based in Barcelona, I work on end-to-end ML automation at I2CAT Foundation, delivering distributed ML pipelines for 5G/IoT and scalable AI services. I enjoy collaborating with research and engineering teams across research-to-production cycles, turning complex problems into robust, scalable systems and continuously improving deployment and performance of ML solutions.…Hi, I’m Juan Sebastian Camargo Barragan, a machine learning engineer focused on building scalable ML pipelines, cloud-native infrastructure, and end-to-end AI solutions. I specialize in MLOps, Kubernetes, Kubeflow, MLflow, and automation across data ingestion, model training, experiment tracking, and deployment to accelerate AI initiatives. Currently based in Barcelona, I work on end-to-end ML automation at I2CAT Foundation, delivering distributed ML pipelines for 5G/IoT and scalable AI services. I enjoy collaborating with research and engineering teams across research-to-production cycles, turning complex problems into robust, scalable systems and continuously improving deployment and performance of ML solutions.

Available to hire

Hi, I’m Juan Sebastian Camargo Barragan, a machine learning engineer focused on building scalable ML pipelines, cloud-native infrastructure, and end-to-end AI solutions. I specialize in MLOps, Kubernetes, Kubeflow, MLflow, and automation across data ingestion, model training, experiment tracking, and deployment to accelerate AI initiatives.

Currently based in Barcelona, I work on end-to-end ML automation at I2CAT Foundation, delivering distributed ML pipelines for 5G/IoT and scalable AI services. I enjoy collaborating with research and engineering teams across research-to-production cycles, turning complex problems into robust, scalable systems and continuously improving deployment and performance of ML solutions.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Language

Spanish; Castilian

Fluent

English

Advanced

Work Experience

MLOps & ML Lifecycle Engineer at I2CAT Foundation

January 1, 2021 - Present

Built end-to-end ML pipelines covering data ingestion, model training, experiment tracking, and deployment. Implemented automated ML workflows using Kubeflow Pipelines, MLflow, Apache Airflow, and Jenkins. Deployed containerized ML services on Kubernetes, orchestrating distributed workloads and scalable inference pipelines. Served models with Ray Serve and REST APIs, and deployed using Helm with CI/CD to ensure reproducibility and rapid iteration.