Java Developer- Ai Training

Job Description

Work Mode: Remote

Engagement Type: Independent Contractor

Schedule: Full-Time or Part-Time Contract

Language Requirement: Fluent English

Role Overview

We 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 Youll Do

Evaluate 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 tools

Annotate 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 guidelines

Who You Are

You hold aBS, MS, or PhD in Computer Science or a closely related field

You 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 Hardlevel problems independently

You 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 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

What Success Looks Like

You 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

Hybrid remote