Mozn is seeking a Senior AI Engineer to lead the design, deployment, and optimization of machine learning and generative AI solutions. This role focuses on applying advanced ML techniques to solve real-world challenges for government and enterprise clients in Saudi Arabia. You will design, build, and scale ML models and the supporting infrastructure; deploy deep learning and generative models into production for public and private sector projects; optimize training and inference for performance, latency, and scalability; monitor, retrain, and improve deployed models; provide expert guidance to client stakeholders; own the end-to-end delivery of AI solutions, including data pipelines, model development, backend services, APIs, integrations, user interfaces, deployment, and operations; build data ingestion, transformation, and processing pipelines for structured and unstructured data; develop backend services and APIs to expose AI capabilities securely; contribute to frontend interfaces and dashboards for AI-powered solutions; integrate AI solutions with enterprise systems, databases, authentication services, and third-party platforms. Requirements include a Bachelor's or Master's degree in computer science or related field; 5+ years of experience across software engineering, ML engineering, data science, data engineering, and generative AI; proficiency with Python, TensorFlow, PyTorch, ONNX, and ML deployment frameworks; experience with Docker, Kubernetes, MLflow, and local LLM deployment frameworks; knowledge of on-premise infrastructure design and enterprise architecture;

Mozn is seeking a Senior AI Engineer to lead the design, deployment, and optimization of machine learning and generative AI solutions. This role focuses on applying advanced ML techniques to solve real-world challenges for government and enterprise clients in Saudi Arabia. You will design, build, and scale ML models and the supporting infrastructure; deploy deep learning and generative models into production for public and private sector projects; optimize training and inference for performance, latency, and scalability; monitor, retrain, and improve deployed models; provide expert guidance to client stakeholders; own the end-to-end delivery of AI solutions, including data pipelines, model development, backend services, APIs, integrations, user interfaces, deployment, and operations; build data ingestion, transformation, and processing pipelines for structured and unstructured data; develop backend services and APIs to expose AI capabilities securely; contribute to frontend interfaces and dashboards for AI-powered solutions; integrate AI solutions with enterprise systems, databases, authentication services, and third-party platforms. Requirements include a Bachelor's or Master's degree in computer science or related field; 5+ years of experience across software engineering, ML engineering, data science, data engineering, and generative AI; proficiency with Python, TensorFlow, PyTorch, ONNX, and ML deployment frameworks; experience with Docker, Kubernetes, MLflow, and local LLM deployment frameworks; knowledge of on-premise infrastructure design and enterprise architecture;