Double atomic catalysts (DACs) have emerged as a promising approach for addressing the shuttle effect and sluggish kinetics in room temperature sodium‐sulfur batteries (RT‐SSBs). However, identifying optimal metal combinations to meet the multiple requirements for RT‐SSBs is challenging. Herein, a method for designing V‐based DACs catalysts (DAC‐VX, X = metal atoms) is presented by distilling descriptors through first‐principle calculations and Multi‐Task Learning‐Sure Independence Screening and Sparsifying Operator. Theoretical calculations reveal the d‐d orbital couplings between V and X significantly influences catalytic performance, highlighting the advantages of DAC‐VX systems over SAV in reducing discharge reaction energy barriers and enhancing anchoring ability, although they are less effective in promoting Na₂S decomposition and Na migration. Moreover, a 3D multifunctional descriptor (Ce, Vm, Ra) is developed, enabling simultaneous prediction of sodium polysulfides adsorption energy, Na2S decomposition energy barrier, Na migration energy barrier, and discharge reaction energy barrier on DAC‐VX, overcoming the limitation of single performance descriptors. Notably, the coexisting SAV and DAC‐VCr are identified as an excellent catalyst candidate, offering the lowest discharge reaction energy barrier (0.54 eV), strong anchoring ability, and the lowest decomposition energy barrier for Na2S (0.96 eV). This work provides valuable insights for data‐driven design of DACs for RT‐SSBs.