Show HN: Automating Job Search with AI

[hubraumhugo]

https://github.com/AdrianKrebs/datalens

This is a personal experiment that uses LLMs to rank unstructured job posting data based on user-defined criteria. Traditional job search platforms rely on rigid filtering systems, but many users lack such concrete criteria.

One of the superpowers of LLMs is understanding unstructured data, like the job postings in the monthly "Ask HN: who's hiring" threads. So I built a little tool that lets you define your preferences in a more natural way and then rates each job postings based on the relevance.

You can define what you're looking for in simple terms and get a custom list ranked by relevance. It's not flawless (especially with cheaper models like gpt-3.5), but it's a lot better than searching through hundreds of listings manually.

[hughdbrown]

As I read it, the code scans listed websites for jobs and scrapes the jobs from each page, possibly using custom code, Is that right? That seems to be the weakness of scraping multiple independent webpages -- that each needs custom code. If you are going to look for jobs on multiple websites, it requires a significant programming effort for each website.

[hubraumhugo → hughdbrown]

I'm using https://Kadoa.com to generate scrapers for any job source in seconds, which removes the bottleneck of having to write and maintain custom code for ever source.

[tough → hughdbrown]

You can use LLM's to parse any html tho