Senior Code Reviewer for LLM Data Training (Java)
Role Overview
As a Senior Code Reviewer at G2i Inc., you will leverage your deep Java expertise to review and audit evaluations of AI-generated Java code completed by data annotators. This senior-level role involves ensuring that code adheres to quality guidelines and providing constructive feedback to maintain high annotation standards, ultimately impacting the integrity of AI training processes.
Perks & Benefits
This position offers a fully remote work setup with flexible hours, allowing for a work-life balance that suits your schedule. Compensation is personalized based on experience and can be re-evaluated for different projects, which supports career growth. You'll work within a culture that values consistent, reliable compensation and recognition of your contributions.
Full Job Description
About the Company
G2i connects subject-matter experts, students, and professionals with flexible, remote AI training work such as annotation, evaluation, fact-checking, and content review. We partner with leading AI teams, and all contributions are paid weekly upon approval, ensuring consistent, reliable compensation.
About the Role
We’re hiring Code Reviewers with deep Java expertise to review evaluations completed by data annotators assessing AI-generated Java code responses. Your role is to ensure that annotators follow strict quality guidelines related to instruction-following, factual correctness, and code functionality.
Responsibilities
Review and audit annotator evaluations of AI-generated Java code.
Assess if the Java code follows the prompt instructions, is functionally correct, and secure.
Validate code snippets using proof-of-work methodology.
Identify inaccuracies in annotator ratings or explanations.
Provide constructive feedback to maintain high annotation standards.
Work within Project Atlas guidelines for evaluation integrity and consistency.
Required Qualifications
5–7+ years of experience in Java development, QA, or code review.
Strong knowledge of Java syntax, debugging, edge cases, and testing.
Comfortable using code execution environments and testing tools.
Excellent written communication and documentation skills.
Experience working with structured QA or annotation workflows.
English proficiency at B2, C1, C2, or Native level.
Preferred Qualifications
Experience in AI training, LLM evaluation, or model alignment.
Familiarity with annotation platforms.
Exposure to RLHF (Reinforcement Learning from Human Feedback) pipelines.
Compensation
Hourly rates are personalized based on your experience level, educational background, location, and industry expertise. You’ll see your specific rate in your contract offer before signing. Rates for technical roles can vary significantly based on these factors and can be re-evaluated for different projects based on your performance and experience with SuperAnnotate.
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