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Hello! I used an LLM to extract structured data from each comment on the “Ask HN: Who is Hiring? (January 2024)” post, available at: <a href="https://news.ycombinator.com/item?id=38842977">https://news.ycombinator.com/item?id=38842977</a>. This created a dataset of 400+ jobs with data such as title, company name, location, is job remote, salary data, and the URL/email to contact. For the UI, a NextJS static site was created to filter and view the structured data.

Funny that only 51 out of 475 jobs show the salary while tech people are very vocal against not showing it.

Good stuff. Remote is not a boolean though. It would be good to specify:* Which countries can apply for the role (or is it Global)* Which timezones can apply for the role (or is it Global)If not specified you could assume you need to be a citizen of their country and in their time zone +/- 3 hours.I think this is where an LLM can shine, it may be able to make good guesses about this stuff.

Nice, a time/date on each comment might be useful, so you can find the jobs posted an hour ago rather than 5 days.

Awesome!Small suggestion, move the "Link to original comment" button, to the HN comment drop-down.

Can we get a "Kubernetes" added to the technologies filter?

Funny that only 51 out of 475 jobs show the salary while tech people are very vocal against not showing it.

Nice, a time/date on each comment might be useful, so you can find the jobs posted an hour ago rather than 5 days.

Awesome!Small suggestion, move the "Link to original comment" button, to the HN comment drop-down.

Can we get a "Kubernetes" added to the technologies filter?

Show HN: I used an LLM to parse HN Who's Hiring comments to structured job data

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Show HN: I used an LLM to parse HN Who's Hiring comments to structured job data

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