@seclink: HARD Non-Code Ultra-Long-Cycle Tasks | Expert Question Designers Recruitment Requirements for This Recruitment 1. No re…
Summary
This article details recruitment requirements for expert question designers to develop non-code, long-cycle tasks for AI model validation, stressing authenticity, quality control, and relevant professional experience.
View Cached Full Text
Cached at: 09/01/26, 01:44 PM
HARD Non-Code Ultra-Long-Cycle Tasks | Expert Question Designers Recruitment
Requirements for This Recruitment
-
No restrictions on industry or professional field, but must possess genuine professional, research, educational, or organizational project experience, and have taken on key responsibilities in relevant projects; only apply for scenarios where you truly have actual experience.
-
Ability to transform real complex work into single-round, non-code long-cycle tasks; the primary task objective must not be developing software, modifying code, or troubleshooting program issues.
-
Tasks must have authenticity and integrity: multiple stages revolve around the same goal and are interdependent, with changes in key data, assumptions, or decisions impacting downstream outcomes.
-
Ability to provide legal, authorized, and desensitized attachments such as documents, tables, interview records, business data, project materials, or reference templates.
-
Ability to independently write exam points, passing criteria, hard failure items, common pitfalls, response strategies, standard or reference answers, and corresponding attachments, while specifying the manual review cycle.
-
Ability to cooperate in frontier model difficulty validation, question duplication checks, quality inspections, supplementary materials, and revisions; questions with excessive similarity or failing quality inspections will not be adopted.
Similar Articles
@seclink: Interested parties, please private message: "Retail Store Operations" Expert—Interview Task ¥800 Hourly Remuneration Pr…
This is a recruitment post for retail store operations experts to participate in 1v1 interviews, aiming to create business scenarios for evaluating AI agent capabilities.
@thaiscbranco_: seeking AI Engineers. not just any AI engineer, one who: - turns model output from slop to *chef's kiss * - obsesses ov…
Recruiter seeks elite AI engineers focused on model output polish, rigorous evaluation, and creative tooling over flashy UI.
@svpino: Some companies are still hiring exclusively with old-fashion questions (no AI involved). Some companies (most that I've…
Some companies are still hiring exclusively with old-fashion questions (no AI involved). Some companies (most that I've seen), are starting to let candidates use AI as part of their interviews. Some companies are exclusively asking questions related to AI-assisted development: harnesses and how to use them, MCP and how to implement or take advantage of them, best way of authoring skills, evaluation techniques, etc. I suspect most companies will eventually move toward the third group. > **Carlos
@AlexGDimakis: I am very excited about this research: We show 2 things: 1. If you just do random sampling (i.e. you try to solve a pro…
This research compares AI coding agents (like Claude-Code and Codex) with human expert coders on long-horizon tasks, showing that humans scale super-linearly due to continual learning while agents plateau, highlighting a key limitation of current AI in extended problem-solving.
@DeRonin_: As an AI engineer in 2026, learn this: > systematic output reading. pattern recognition across 1,000 model responses is…
A seasoned AI engineer shares key skills for 2026, including systematic output reading, context engineering, tool description discipline, eval design, model routing, prompt versioning, confidence scoring, streaming architecture, fallback chains, latency budgets, failure cataloguing, agent-vs-workflow decisions, and failure post-mortems as portfolio content.