Could probably do an elo system and sample pairs. E.g.

1. Set the elo of all CVs to 1000 elo

2. Randomly pair up CVs and compare. Winners gain elo, losers lose elo.

3. Repeat #2 for a few iterations, then remove bottom X% of CVs.

4. Repeat 2-3 until the amount of remaining CVs is small enough to do an exhaustive comparison.

I don't have a mathematical proof, but I suspect that this is a decent cost-effective approximation of comparing every pair (depending on the parameters)

> you should compare every pair of CVs for best results

Or compare each one to a reference set? Take 5 resumes of existing employees, rank all candidates against that set, maybe you get some useful level prediction into the bargain

I'd just do a quick filter, probably deterministic, then perform a deeper comparison on the selected few.