An application made for this job — a tailored resume and cover letter that speak straight to the posting.
AI Trainer Jobs seeks a remote Game Developer (Cocos2d-x) reviewer to evaluate production code, debug traces, and AI outputs for real-world correctness. You will reproduce failures, write unit tests the model should have written, and explain the fix so the modeling team can target gaps.
Responsibilities include running code in a sandbox, grading solutions for correctness and edge-cases, and writing minimal failing tests.
Game Developer (Cocos2d-x) is a remote engineering review track for evaluating production code, debugging traces, and developer-facing AI outputs against real-world correctness standards. Reviewers reproduce failures, write the unit test the model should have written, and explain the fix so the modeling team can target the gap.
Category: Coding, SWE & Agent Evaluation · Pay: $130 / hr · Location: Remote — US-eligible · Contractor
Game Developer (Cocos2d-x) is a remote engineering review track for evaluating production code, debugging traces, and developer-facing AI outputs against real-world correctness standards.
Game Developer (Cocos2d-x) is a remote engineering review track for evaluating production code, debugging traces, and developer-facing AI outputs against real-world correctness standards. Reviewers reproduce failures, write the unit test the model should have written, and explain the fix so the modeling team can target the gap.
Engineering model quality lives or dies on whether the generated code actually compiles, passes tests, and handles edge cases. AuraOne pairs experienced engineers with the modeling team to grade outputs the way a code reviewer would.
Judge generated code and software engineering agents. Read their debugging traces.
Track Code review & evaluation Work model Remote · Independent specialist contractor Compensation Hourly rate confirmed after the interview process. Eligible from US
Hourly rate confirmed after the interview process.
Expected arrangement: contractor , with program‑defined task volume and review pacing. Placement depends on current program demand and reviewer confirmation.