{"html":"<p>In this hourly, remote contractor role, you will work as a C++ Quality Assurance Lead (QAL) to oversee quality, consistency, and trainer performance across C++ AI training projects. You will review AI-generated C++ code and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure contributors follow expected quality standards.</p>\n<p>You will assess work for code correctness, compile-time validity, runtime behavior, memory safety, performance, algorithmic reasoning, debugging accuracy, readability, maintainability, formatting, instruction-following, and adherence to project-specific rubrics. This role requires strong C++ expertise, English communication skills, excellent attention to detail, and the ability to manage quality workflows across remote technical teams.</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 C++ quality leadership will help ensure C++ training data is accurate, compilable, efficient, safe, 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>Quality monitoring: Spot-check C++ items, identify issues, provide feedback through DMs, and escalate recurring or critical quality problems.</li><li>Code review: Evaluate AI-generated C++ code, debugging responses, algorithmic solutions, tests, explanations, and performance recommendations.</li><li>Trainer/QA communication: Update contributors on Discord about guideline changes, workflow updates, and C++-specific review standards.</li><li>Question handling: Respond to questions around memory safety, compilation, templates, STL usage, concurrency, complexity, testing, and rubric interpretation.</li><li>Activation management: DM inactive contributors, track follow-ups, and flag availability issues.</li><li>Documentation: Create and maintain C++ style guides, trackers, FAQs, examples, honeypots, calibration tasks, and onboarding materials.</li><li>Onboarding: Run onboarding/training calls covering project expectations, rubrics, and C++ quality standards.</li><li>Risk review: Flag unsafe, non-compilable, misleading, inefficient, or non-production-ready C++ recommendations.</li><li>Process improvement: Identify recurring quality gaps and build scalable QA processes.</li></ul><h3>Requirements</h3><ul><li>Bachelor’s or Master’s degree in Computer Science, Software Engineering, Computer Engineering, or equivalent professional software engineering experience.</li><li>Strong grasp of English to follow guidelines and provide clear technical feedback.</li><li>3+ years of professional experience in C++ development, systems programming, performance engineering, embedded software, backend engineering, code review, QA, or technical mentoring.</li><li>Strong understanding of modern C++ standards, RAII, smart pointers, templates, STL containers/algorithms, object lifetime, move semantics, concurrency, exceptions, memory management, and build systems.</li><li>Ability to identify issues such as undefined behavior, memory leaks, dangling references, race conditions, inefficient algorithms, non-compilable code, hallucinated APIs, or incomplete explanations.</li><li>Familiarity with CMake, GCC/Clang/MSVC, GDB/LLDB, sanitizers, Valgrind, GoogleTest, Catch2, Boost, GitHub, CI/CD, profiling, and static analysis tools is preferred.</li><li>Experience leading or supporting remote teams of trainers, reviewers, engineers, coding mentors, or QAs is strongly preferred.</li><li>Comfortable using Discord, Google Sheets, Google Docs, trackers, dashboards, GitHub, and project management systems.</li><li>Highly organized and able to maintain style guides, FAQs, trackers, onboarding materials, honeypots, calibration tasks, and quality documentation.</li><li>Experience with AI training, data annotation, LLM evaluation, code QA, or rubric-based code review is a strong plus.</li></ul>"}