How to create a model to suggest similar words in realtime?
Autocompletion algorithms usually build on either tree or hash structure for the sake of efficiency. One famous approach is the Ternary Search Tree. Use this source to have an initial idea. It is also a comparably space-efficient solution. You can find more complex systems build on the Ternary Search Tree.
Another good solution is Trie. Trie data structure is a good alternative of Ternary Search Trees, as an example implementation check this.
These both are handy at the front end of the application since they are simple but powerful approaches. Other than that, they have a good balance of time and space complexity.
Moreover, a fast-autocomplete library may help you. Since, in your case, you may have two names for the same job, it has synonym functionality.
In general, tree structures are what you are looking for. You can do this task even using Binary Trees. However, I would suggest you consider the case that in reality many times there appears spelling problems, so in that case, you either will not be able to suggest a word or the suggestion will be incorrect. For such problems, you can also have a spelling check algorithm that first checks if such a word exists, if not using spell check you can have proposed words and you can suggest the autocompletion based on those suggestions. E.g. instead of 'Java' one may type in 'Jsva' and your algorithm will find the correct word and make the suggestion accordingly. This is a one-of-the best algorithms that does auto-completion using ML techniques. You can also build a simple one using Levenshtein distance. (However, spelling error cases mostly discarded in the systems because of its being costly to fix them)