[job_card.job_description]Location :N / AType: Full-time or Part-time Contract WorkFluent Language Skills Required :EnglishWhy This Role ExistsMercor partners with leading AI teams to improve the quality, usefulness, and reliability of general-purpose conversational AI systems. These systems are used across a wide range of everyday and professional scenarios, and their effectiveness depends on how clearly, accurately, and helpfully they respond to real user questions. In coding and software engineering contexts, conversational AI systems must demonstrate correct reasoning, strong problem-solving ability, and adherence to real-world engineering best practices. This project focuses on evaluating and improving how models reason about code, generate solutions, and explain technical concepts across a variety of programming tasks and complexity levels.What You’ll DoEvaluate LLM-generated responsesto coding and software engineering queries for accuracy, reasoning, clarity, and completeness -Conduct fact-checkingusing trusted public sources and authoritative references - Conduct accuracy testing byexecuting code and validating outputs using appropriate toolsAnnotate model responsesby identifying strengths, areas of improvement, and factual or conceptual inaccuracies - Assess code quality, readability, algorithmic soundness, and explanation quality - Ensuremodel responses align with expected conversational behaviorand system guidelines -Apply consistent evaluation standardsby following clear taxonomies, benchmarks, and detailed evaluation guidelinesWho You AreYou hold aBS, MS, or PhD in Computer Science or a closely related fieldYou havesignificant real-world experience in software engineeringor related technical roles - You are an expert in atleast one relevant programming language (e.g., Python, Java, C++, JavaScript, Go, Rust)You are able to solveHackerRank or LeetCode Medium and Hard–level problems independentlyYou have experience contributing to well-known open-source projects, including merged pull requests - You havesignificant experience using LLMs while codingand understand their strengths and failure modes -You have strong attention to detailand arecomfortable evaluating complex technical reasoning, identifying subtle bugs or logical flawsNice-to-Have SpecialtiesPrior experience with RLHF, model evaluation, or data annotation work - Track record in competitive programming - Experience reviewing code in production environments - Familiarity with multiple programming paradigms or ecosystems - Experience explaining complex technical concepts to non-expert audiencesWhat Success Looks LikeYou identify incorrect logic, inefficiencies, edge cases, or misleading explanations in model-generated code, technical concepts, and system design discussions - Your feedback improves the correctness, robustness, and clarity of AI coding outputs - You deliver reproducible evaluation artifacts that strengthen model performance - Mercor customers trust AI systems to assist reliably with real-world coding tasksWhy Join MercorAt Mercor, experienced software engineers play a direct role in shaping how AI systems reason about and generate code. This flexible, remote role allows you to apply your technical expertise to high-impact AI development work, improving systems used by developers around the world.