I don't believe so. The two main problems of interest in the Cayley table model are membership testing and isomorphism testing. Membership testing belongs to $\textsf{L}$ by reduction to path finding on an appropriate Cayley graph.
Isomorphism testing belongs to $\beta_{2}\textsf{L} \cap \beta_{2}\textsf{FOLL} \cap \beta_{2}\textsf{SC}^{2}$ by the generator enumeration strategy. Every group has a generating set of size at most $O(\log n)$ (and a cube generating set of size $O(\log n)$), and so we can guess a generating set with $O(\log^{2} n)$ bits and then perform marked isomorphism testing efficiently in parallel. The $\beta_{2}\textsf{FOLL}$ and $\beta_{2}\textsf{SC}^{2}$ bounds rely on guessing cube generating sequences.
It is known that $\beta_{2}\textsf{FOLL}$ cannot compute Parity. As Parity is $\textsf{AC}^{0}$-reducible to Graph Isomorphism, this shows that Group Isomorphism is strictly easier than Graph Isomorphism.
Furthermore, there is considerable evidence that Graph Isomorphism is not $\textsf{NP}$-complete. All of this evidence applies to Group Isomorphism as well.
Also, Tensor Isomorphism problems in the multidimensional array (verbose) model have the same upper bounds as Graph Isomorphism. So even these much harder problems are unlikely to be NP-complete. (https://arxiv.org/pdf/1907.00309.pdf)