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| # Problem & Evaluation Mechanics | |
| > Part of the MochiRank docs. See [architecture/spec.md](../architecture/spec.md) for the system design. | |
| ## 1. Problem Restatement (Read Between the Lines) | |
| The JD is a 2000-word essay for **Senior AI Engineer β Founding Team** at Redrob AI. | |
| The hidden note at the bottom of the JD (for hackathon participants) is the real brief: | |
| > "The right answer involves reasoning about the **gap between what the JD says and what the JD means**. | |
| > A Tier 5 candidate may not use the words 'RAG' or 'Pinecone' but if their career shows they built | |
| > a recommendation system at a product company, they're a fit. A perfect-on-paper candidate who hasn't | |
| > logged in for 6 months and has a 5% recruiter response rate is not actually available." | |
| Four trap types are explicitly built into the 100K dataset: | |
| - **Keyword stuffers** β skills list has every AI keyword, but career history doesn't support them | |
| - **Plain-language Tier 5s** β great candidate, zero buzzwords in their profile | |
| - **Behavioral twins** β near-identical profiles, differ only in `redrob_signals` | |
| - **~80 honeypots** β internally inconsistent profiles (>10% honeypot rate in top-100 = disqualification) | |
| These traps map directly to architectural decisions. Pure embedding cosine similarity fails all four. | |
| ## 2. Evaluation Mechanics (What Actually Scores Points) | |
| ``` | |
| composite = 0.50 Γ NDCG@10 + 0.30 Γ NDCG@50 + 0.15 Γ MAP + 0.05 Γ P@10 | |
| ``` | |
| **50% of the score is the top 10.** Find the 5β10 genuinely great candidates out of 100K. | |
| Volume of mediocre-middle candidates barely moves the needle. Optimize for precision at the top. | |
| **Stage 3 reproduction kills most submissions.** Must reproduce inside Docker: 5 min wall-clock, | |
| 16 GB RAM, CPU only, zero network. Plan for this from day one. | |
| **Stage 4 reasoning checks** (if you reach top-N) sample 10 rows and check for: | |
| specificity, JD connection, honest concerns, no hallucination, variation, rank-consistency. | |
| If reasoning is mechanically derived from the model's actual decision, all 6 checks pass automatically. | |