Posted at: 25 November
Senior Code Reviewer for LLM Data Training (Java)
Company
G2i
G2i is a U.S.-based B2B SaaS platform specializing in connecting companies with top engineering talent, including software engineers and AI specialists.
Remote Hiring Policy:
G2i is a fully remote company hiring engineers for contract roles worldwide, with team members located in various regions such as LATAM, Europe, and Canada.
Job Type
Full-time
Allowed Applicant Locations
Worldwide
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.