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**Role:** Java Software Engineer – Ai Training
**Company:** YO IT Consulting
**Location:** Georgia (Remote)
**Engagement Type:** Independent Contractor
**Schedule:** Full-Time or Part-Time Contract
**Language Requirement:** Fluent English
**Role Overview:**
Partner with leading AI teams to improve the quality, usefulness, and reliability of general-purpose conversational AI systems. This project focuses on evaluating and improving how AI systems reason about code, generate programming solutions, and explain technical concepts. The role involves rigorous technical evaluation of AI-generated responses in coding and software engineering contexts.
**Responsibilities:**
* Evaluate LLM-generated responses to coding and software engineering queries for accuracy, reasoning, clarity, and completeness.
* Conduct fact-checking using trusted public sources and authoritative references.
* Perform accuracy testing by executing code and validating outputs using appropriate tools.
* Annotate model responses by identifying strengths, areas of improvement, and factual or conceptual inaccuracies.
* Assess code quality, readability, algorithmic soundness, and explanation quality.
* Ensure model responses align with expected conversational behavior and system guidelines.
* Apply consistent evaluation standards by following clear taxonomies, benchmarks, and detailed evaluation guidelines.
**Qualifications:**
* BS, MS, or PhD in Computer Science or a closely related field.
* Significant real-world experience in software engineering or related technical roles.
* Expertise in at least one relevant programming language (e.g., Python, Java, C++, JavaScript, Go, Rust).
* Ability to independently solve HackerRank or LeetCode Medium and Hard-level problems.
* Experience contributing to well-known open-source projects, including merged pull requests.
* Significant experience using LLMs while coding and understanding their strengths and failure modes.
* Strong attention to detail and comfort evaluating complex technical reasoning and identifying subtle bugs or logical flaws.
**Nice-to-Have Specialties:**
* Prior 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 audiences.
**Success Metrics:**
* Identifying incorrect logic, inefficiencies, edge cases, or misleading explanations in model-generated code, technical concepts, and system design discussions.
* Improving the correctness, robustness, and clarity of AI coding outputs through feedback.
* Delivering reproducible evaluation artifacts that strengthen model performance.