We've developed an AI- and machine learning-driven IC design orchestration project to tackle the challenges of modern hardware systems, enabling fast and effective design space exploration while reducing computational resources demand. Our approach involves containerizing the digital design flow on a hybrid cloud platform, utilizing Kubernetes clusters for scalable execution and Helm for cloud resource management. We've also developed an ML-driven automatic parameter tuner that leverages Ray and Ray Tune to identify optimal design settings, achieving significant improvements in quality of results compared to manual tuning by expert designers.