AI Code Reviewer & Annotator

Responsibilities - All work must be your own. Use of LLMs or other AI tools to generate, assist with, or complete tasks is strictly prohibited — this data is used to train and evaluate AI models, so AI-generated submissions defeat the purpose, are detectable, and are grounds for removal. - Evaluate code samples from simulated LLM conversations — select the strongest option and clearly explain your reasoning. - Curate and annotate code snippets for training data across tasks such as code generation from natural language, code completion/infilling, debugging and repair (using both natural-language and program context), and code translation, refactoring, summarization, and documentation. - Perform quality assurance on peer-generated content to ensure it meets accuracy, clarity, and technical standards. Requirements: - Strong coding proficiency in one or more of: Go, Rust, C#, C++, Kotlin, or Ruby. - Excellent written English, especially for explaining technical concepts clearly and concisely. - Comfortable working in code editors, spreadsheets, and browser-based annotation/QA tools.