Machine Learning, Unsupervised Learning, Python, agentic AI, adversarial machine learning, debugging complex ML failure modes, reverse engineering model behaviors, supervised learning, generative models, reinforcement learning, data poisoning, ML safety, evaluating frontier AI systems, prompt injection, ML interpretability, multi-object optimization, adversarial robustness, model backdoor detection, adversarial machine learning AI agent security, red-teaming frontier AI systems