Suggestions for Molecular-Like Systems (not periodic unit cells)
I'll make some general suggestions for molecular / isolated systems, not crystals. (In the case of periodic systems, some methods aren't available or are different.)
You mentioned increasing the number of self-consistent steps. If your SCF calculation doesn't converge, there are a variety of separate questions / methods to try.
The main problem is that getting to a final equilibrium geometry with a DFT or high-level wavefunction method can be slow. For larger systems, there are many degrees of freedom and often the potential energy surface is fairly flat, especially with dihedral angles.
So the goal is to get close to a converged geometry with a faster method, then to switch eventually to your method of choice.
Years ago, the advice would be to use a force field to "pre-optimize" a system, since these are intended to get quality geometries. I no longer advise this unless you have a specialized force field (e.g., biomolecule force fields work well for biomolecules).
In particular in two benchmark papers, we found that force field methods weren't very good:
We found that the MMFF94-optimized geometries had large forces when you switched to semiempirical or DFT methods. We also found that when ranking different conformer poses by energy, the force field had poor correlation with ab initio methods.
Instead, we find much better results with the approximate GFN2 / xtb method, or if possible with methods like ANI-2x, with the caveat that GFN2 works for all elements.
Our most recent workflow is something like this:
Generate an initial geometry (e.g. in Avogadro, RDKit, etc.)
Optimize the geometry using xtb which is fast and often "forgiving" (e.g., easier to converge SCF).
Optimize the geometry using B97-3c or similar GGA method (e.g. r$^2$SCAN-3c looks good too)
Optimize the geometry in your favorite method with dispersion correction (e.g., $\omega$B97X-D4 or $\omega$B97M-V for example, triple-zeta basis set).
If step 4 still takes a long time or fails to converge, we'll often optimize with def2-SVP first (often with looser convergence criteria) and then switch to the larger basis set.
It's a process - in part because getting the electrostatic and non-covalent interactions right is hard. Some ML-based methods may help with this in the future, but beyond ANI, they are not widely available.