As an ML Engineer and AI Solutions Architect, I design and deploy robust, end-to-end AI solutions. At Telecom Argentina, I lead the design of our private AI/ML infrastructure, building a hybrid, Kubernetes-based cloud for GPU-accelerated workflows with frameworks like OpenShift and Kubeflow. My focus is on creating scalable MLOps pipelines and integrating state-of-the-art models—including Generative AI—into secure and cost-effective business applications.

My hands-on expertise spans a range of applications, from engineering complex, CUDA-optimized speech analytics services and predictive maintenance models to developing computer vision systems for object detection. I specialize in advancing projects from initial baselines to cutting-edge model deployment, ensuring high performance and seamless integration.

• Languages

  • Python | MATLAB | Bash

• Frameworks

  • Scientific computation Numpy | SciPy | CUDA | ROCm
  • Data manipulation & visualization Pandas | Polars | Matplotlib | Seaborn
  • ML & Deep Learning PyTorch | LightningAI | Scikit-Learn | TensowFlow | Keras | Hugging Face

• Platforms

  • AWS | GCP | OpenShift | Kubeflow | Git | Kubernetes

• Tools

  • Docker | Podman | JupyterLab | Colab | VS Code | FastAPI | Flask | Redis | Kafka