We introduce MEET-MR (Machine Translation English–Thai MQM and Ranking Dataset), a comprehensive benchmark for evaluating English–Thai machine translation systems. The dataset is constructed using the Multidimensional Quality Metrics (MQM) annotation framework, providing fine-grained human judgements of translation quality. In addition, MEET-MR includes human preference rankings and reference translations, enabling both absolute and relative assessment of translation quality. The dataset covers nine diverse domains providing linguistic and contextual diversity. By combining high-quality reference translations, objective MQM error annotations, and subjective preference rankings, MEET-MR serves as a valuable resource for studying translation quality estimation, model alignment with human evaluation, and cross-domain performance in English–Thai machine translation. MEET-MR is publicly available at https://huggingface.co/datasets/Chula-AI/MEET-MR