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Python Developer - Ai Training
San Jose, CAMarch 27th, 2026
Work Mode: RemoteEngagement Type: Independent ContractorSchedule: Full-Time or Part-Time ContractLanguage Requirement: Fluent EnglishRole OverviewWe partner with leading AI teams to improve the quality, usefulness, and reliability of general-purpose conversational AI systems. This project focuses specifically on evaluating and improving how AI systems reason about code, generate programming solutions, and explain technical concepts across various complexity levels. The role involves rigorous technical evaluation of AI-generated responses in coding and software engineering contexts.What You'll DoEvaluate LLM-generated responses to coding and software engineering queries for accuracy, reasoning, clarity, and completenessConduct fact-checking using trusted public sources and authoritative referencesConduct accuracy testing by executing code and validating outputs using appropriate toolsAnnotate model responses by identifying strengths, areas of improvement, and factual or conceptual inaccuraciesAssess code quality, readability, algorithmic soundness, and explanation qualityEnsure model responses align with expected conversational behavior and system guidelinesApply consistent evaluation standards by following clear taxonomies, benchmarks, and detailed evaluation guidelinesWho You AreYou hold a BS, MS, or PhD in Computer Science or a closely related fieldYou have significant real-world experience in software engineering or related technical rolesYou are an expert in at least one relevant programming language (e.g., Python, Java, C++, JavaScript, Go, Rust)You are able to solve HackerRank or LeetCode Medium and Hard-level problems independentlyYou have experience contributing to well-known open-source projects, including merged pull requestsYou have significant experience using LLMs while coding and understand their strengths and failure modesYou have strong attention to detail and are comfortable evaluating complex technical reasoning, identifying subtle bugs or logical flawsNice-to-Have SpecialtiesPrior experience with RLHF, model evaluation, or data annotation workTrack record in competitive programmingExperience reviewing code in production environmentsFamiliarity with multiple programming paradigms or ecosystemsExperience 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 discussionsYour feedback improves the correctness, robustness, and clarity of AI coding outputsYou deliver reproducible evaluation artifacts that strengthen model performanceJ-18808-Ljbffr
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