Original Summary

I'm a data engineer in Luxembourg. Job search here is spread across lots of career sites in English, French and German, so I built https://jobs.atync.com . How it works: Ingestion: daily pull from public career-board feeds (Greenhouse, Lever, SmartRecruiters, Personio, Ashby…) plus a couple of job APIs, mapped to one schema, deduplicated, expired after a week. Instant path: hard filters in code (country, work mode, contract, language, years of experience) + multilingual embeddings for a rough ranking. Deep path: you leave your e-mail, requests are batched a few times a day, and an open 2B decision model answers typed yes/no questions about each job vs. your profile. Code combines the answers with fixed weights into Strong / Good / Stretch bands with reasons. You get an e-mail with the results. Design choices I'd love opinions on: - Anything numeric (years, dates) stays in code, never in the model - Batching instead of instant results to keep GPU cost near zero - No name/photo/age/gender/nationality collected; profile deleted after results are sent On ~270 labelled job/profile pairs it hits the exact band about 3 in 4 times and is almost always within one band. Feedback welcome, especially on the match quality and the onboarding form.   submitted by   /u/Charming-Carpet-3874 [link]   [comments]

  • 情报分类：工作与职业机会
  • 分类依据：内容涉及招聘、求职或职业发展
  • 信息来源：Reddit · SideProject
  • 发布时间：2026/10/13 17:59:54