{"html":"<p>In this hourly, remote contractor role, you will work as a Kotlin Quality Assurance Lead (QAL) to oversee quality, consistency, and trainer performance across Kotlin AI training projects. You will review AI-generated Kotlin code and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure contributors follow expected standards.</p>\n<p>You will assess work for code correctness, type safety, coroutine behavior, Android/JVM awareness, debugging accuracy, readability, maintainability, performance, security, test coverage, formatting, instruction-following, and rubric adherence.</p>\n<p>This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Your Kotlin quality leadership will help ensure Kotlin training data is accurate, executable, idiomatic, clearly explained, and aligned with client expectations.</p>\n<p>Selection process involves an AI interview, a domain-specific task, and an interview with a recruiter.</p>\n<p>Important:\nThere is no immediate project for this role; however, if qualified, you will be among the first experts we reach out to when relevant opportunities arise. This will also provide you with access to future projects available through our expert network.</p>\n<h3>Responsibilities</h3><ul><li>Spot-check Kotlin items and provide ongoing feedback through DMs.</li><li>Review AI-generated Kotlin code, Android/JVM snippets, coroutine workflows, tests, and explanations.</li><li>Communicate guideline changes and Kotlin-specific standards on Discord.</li><li>Answer questions around Kotlin syntax, null safety, coroutines, Android/JVM context, tests, packages, and rubric interpretation.</li><li>DM inactive contributors and manage activation tracking.</li><li>Create Kotlin documentation, style guides, examples, trackers, FAQs, honeypots, and onboarding materials.</li><li>Run onboarding/training calls for Kotlin contributors.</li><li>Flag insecure, misleading, non-executable, or non-production-ready Kotlin recommendations.</li><li>Improve QA processes based on recurring quality gaps.</li></ul><h3>Requirements</h3><ul><li>Bachelor’s or Master’s degree in Computer Science, Software Engineering, IT, or equivalent professional experience.</li><li>Strong grasp of English to follow guidelines and provide clear technical feedback.</li><li>3+ years of professional experience in Kotlin, Android development, JVM backend development, code review, QA, or technical mentoring.</li><li>Strong understanding of Kotlin syntax, null safety, data classes, sealed classes, generics, extension functions, collections, lambdas, coroutines, flows, exception handling, and interoperability with Java.</li><li>Ability to identify issues such as incorrect coroutine usage, non-idiomatic Kotlin, unsafe null handling, flawed logic, non-executable code, hallucinated APIs, or incomplete explanations.</li><li>Familiarity with Android, Jetpack Compose, Gradle, Ktor, Spring Boot, JUnit, MockK, Espresso, Kotlin Flow, GitHub, CI/CD, and app architecture patterns is preferred.</li><li>Experience leading or supporting remote teams of trainers, engineers, reviewers, or QAs is strongly preferred.</li><li>Comfortable with Discord, Google Sheets, Google Docs, trackers, dashboards, GitHub, and PM systems.</li><li>Highly organized and able to maintain style guides, trackers, FAQs, honeypots, calibration tasks, and onboarding materials.</li><li>Experience with AI training, LLM evaluation, code QA, or rubric-based code review is a strong plus.</li></ul>"}