The intersection of novel design and manufacturing processes for metamaterials has demonstrated how modern technologies can shape their development. This chapter includes an in-depth discussion on topology optimization, highlighting the integration of physics-based machine learning algorithms. These algorithms play a crucial role in predicting and determining the material properties based on the intended intricate geometries prior to manufacturing, ensuring optimal functionality. Electrochemical fabrication is explored as a pivotal method for creating advanced cloaking and electrochemically responsive metamaterials. The precision and scalability provided by this technique are essential for crafting the richly detailed formations that these materials require. The impact of additive manufacturing is transformative in this field, which facilitates the creation of highly intricate customized three-dimensional geometries. This process-controlled method allows for unprecedented customization and complexity in metamaterial design. Furthermore, traditional manufacturing techniques continue to play a significant role in the production of metamaterials. It examines how these conventional methods are being adapted and integrated with new technological advances to meet the demands of modern metamaterial applications. Additionally, the challenges and opportunities presented by these manufacturing techniques, including scalability, and material limitations are covered.