What should I check if model accuracy is no better than baseline level(random guess)
This is a common problem with rare events modelling, and your options are relatively limited (as far as I am aware, at least). It may well be the case that the features you're using are not very informative with respect to predicting these outcomes.

The major issue is that your predictors, in the context of this model, are not very informative. The model tries to balance false positives and false negatives, but with so few true positives any mistakenly-predicted positive outcome will have a large effect on your classification accuracy.

It seems likely in this case that your predictors do not offer enough information to predict outcomes well. You may have reached the ceiling of what this model can do. This could be an artifact of the rarity of the "hired" outcome in your data set, or it could simply be that the relationship between these predictors and the outcome is weak.

There are a few options, involving use of different techniques (like a Firth regression, designed for rare events modelling). But using different predictors may be the best option, if it is possible to do so. Not every event can be modelled well with some arbitrary set of features, and it may be that you've found one of those.