Job searches benefit from understanding industry specific synonyms and reading between the lines. That should be something a large language model could be good at.
For example, if I am searching for “senior front end web developer”, it may return a listing for “experienced software engineer” because it lists “5-7 years experience with JavaScript”. It could also list adjacent fields the user may want to consider like Project Management or being a Technical Account Manager for the right type of company.
Also, the risk of AI slop is fairly harmless. If done right, the AI should not be hallucinating job listings. At worst, it can show irrelevant listings while hiding good ones, but that is always a risk with search engines. The developers can mitigate this by mixing results from both the AI and conventional search engine and let the user provide feedback if a listing is relevant or not.
Job searches benefit from understanding industry specific synonyms and reading between the lines. That should be something a large language model could be good at.
For example, if I am searching for “senior front end web developer”, it may return a listing for “experienced software engineer” because it lists “5-7 years experience with JavaScript”. It could also list adjacent fields the user may want to consider like Project Management or being a Technical Account Manager for the right type of company.
Also, the risk of AI slop is fairly harmless. If done right, the AI should not be hallucinating job listings. At worst, it can show irrelevant listings while hiding good ones, but that is always a risk with search engines. The developers can mitigate this by mixing results from both the AI and conventional search engine and let the user provide feedback if a listing is relevant or not.