This paper introduces ML-Master 2.0, an autonomous agent designed for ultra-long-horizon machine learning engineering. It leverages Hierarchical Cognitive Caching (HCC) to manage context through cognitive accumulation, achieving a state-of-the-art 56.44% medal rate on OpenAI's MLE-Bench.