Java AI Data Training Tech Quality Lead | Remote

Java AI Data Training Tech Quality Lead Work SnapshotJob Type: ContractLocation: Remote (United States)Compensation: $50 $100 per hourCommitment: Flexible / project-based (hourly) Roles & ResponsibilitiesReview Java code submissions and AI-generated solutions for correctness, readability, maintainability, and adherence to coding standardsEvaluate algorithmic soundness, debugging approaches, performance implications, modularity, and software engineering best practicesProvide detailed and constructive feedback on Java tasks while escalating critical technical or quality issues when necessaryMaintain high-quality standards for AI training data and Java-focused coding workflowsCommunicate project updates, review expectations, and technical clarifications with trainers and QA contributorsMonitor contributor engagement and proactively support inactive team members to improve participation and workflow consistencyCreate and maintain documentation including Java coding guidelines, review checklists, example solutions, trackers, FAQs, and onboarding materialsOrganize and conduct onboarding and training sessions focused on Java quality standards, code review practices, and AI training expectations RequirementsEducation: Bachelor s or Master s degree in Computer Science, Software Engineering, or a related field7+ years of professional experience in Java development with strong expertise in code quality review, debugging, technical evaluations, and software maintainabilityStrong understanding of Java programming concepts, system design, implementation approaches, code refactoring, and best practices for robust and readable software developmentHands-on experience with LLM projects, AI training workflows, data annotation, or technical QA processes preferredExcellent analytical and problem-solving skills with the ability to identify root causes, evaluate alternative solutions, and maintain high review accuracyStrong English communication skills (C1 or above) for documentation, async collaboration, and technical feedback across global teamsLeadership mindset with the ability to work independently, mentor contributors, maintain QA standards, and support trainer engagement throughout the review process