The tutorial explores key security and functional safety challenges for Artificial Intelligence (AI) in embedded automotive systems, including aspects from adversarial attacks, long life cycles of products, and limited energy resources of automotive platforms within safety-critical environments in diverse use cases. It provides a set of recommendations for how the security and safety engineering of machine learning can address these challenges. It also provides an overview of contemporary security and functional safety engineering practices, encompassing up-to-date legislative and technical prerequisites. Finally, we identify the role of AI edge processing in enhancing security and functional safety within embedded automotive systems.