Rest of the ones with good scores (at least more than 40K), was reviewed manually.

Reading this thread, I'm hoping to minimize the variability even further (even though I know it can't be fully removed).

There's no better feeling than building something open source and watching it take off. Nine months ago, I built a simple hiring agent to solve one very real problem.

Things it is not: It's not an ATS. We don't use it to screen our open roles. Our customers don't use it either.

Here's what it is: Every year at HackerRank, we get 50,000 to 60,000 intern applications. No human can read that many resumes well. So I built something to rank them, helping me decide which resumes to read first.

[This was before we built AI Interviewer (Chakra) to automate the first round of interviews, so candidates are no longer rejected based on their resumes alone.]

Two things worth clarifying since I've seen them come up in this thread:

The default model is gemma3:4b because it's what runs locally on most laptops - no cloud API needed. Actual resumes are evaluated using a top Gemini model. The repo ships with a demo config, not the production one.

The cutoff score was set very low — the system was designed to rank resumes, not reject them. Only resumes at the very bottom of the distribution were filtered out. The vast majority passed through to human review, where the real decisions were made.

Over the last week, it's taken on a life of its own. People are cloning it, running their own resumes through it, opening issues, sending PRs.

I contributed to open source a lot in college. Somewhere along the way, I drifted away from it. This week reminded me how good that feeling is. This thread has also given me more ideas than I expected. The critiques here are sharp and I'm already thinking about how to act on them. Improvements are coming.

Comments URL: https://news.ycombinator.com/item?id=16280603

Points: 1

# Comments: 0

Totally agree with your 4th point. Unless you actually write code, nothing will help you..