Dhia N.

I specialize in developing and deploying machine learning systems that bridge the gap between research and production. With three years of experience, I excel in the entire MLOps lifecycle, employing tools such as TensorFlow, PyTorch, and HuggingFace to build models and using Docker, Kubernetes, and AWS for scalable deployment. My focus is on creating modular and efficient architectures with FastAPI, Flask, and LangChain, automating workflows with Apache Airflow, and ensuring robust management through MLflow. I design continuous integration and delivery pipelines using GitHub Actions, integrate thorough unit testing, and monitor production systems with Prometheus for high reliability. I thrive on tackling complex challenges and am always eager to learn new technologies that can enhance my work. If you need a proactive AI engineer who can turn ideas into impactful solutions, let’s connect.