{"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 programming 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, pointer logic, portability, performance, debugging accuracy, readability, formatting, instruction-following, and rubric adherence. This role requires strong C expertise, English communication skills, 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, safe, efficient, 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 quality issues, provide feedback through DMs, and escalate recurring or critical issues.</li><li>Code review: Evaluate AI-generated C code, debugging responses, pointer/memory examples, algorithmic solutions, tests, and technical explanations.</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 pointers, memory allocation, compilation, UB, portability, embedded constraints, 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 for C contributors.</li><li>Risk review: Flag unsafe, non-compilable, misleading, memory-unsafe, or non-production-ready C recommendations.</li><li>Process improvement: Identify recurring quality gaps and improve QA workflows.</li></ul><h3>Requirements</h3><ul><li>Bachelor’s or Master’s degree in Computer Science, Software Engineering, Computer Engineering, Electrical Engineering, 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 C programming, systems programming, embedded development, firmware, operating systems, performance engineering, code review, QA, or technical mentoring.</li><li>Strong understanding of pointers, arrays, memory allocation, structs, function pointers, preprocessor macros, header files, compilation/linking, undefined behavior, file I/O, bitwise operations, and portability.</li><li>Ability to identify issues such as buffer overflows, memory leaks, use-after-free, undefined behavior, invalid pointer arithmetic, race conditions, non-compilable code, hallucinated APIs, or incomplete explanations.</li><li>Familiarity with GCC/Clang/MSVC, Make/CMake, GDB/LLDB, Valgrind, sanitizers, embedded toolchains, POSIX APIs, unit testing frameworks, 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 PM systems.</li><li>Highly organized and able to maintain style guides, trackers, FAQs, onboarding materials, honeypots, calibration tasks, and quality documentation.</li><li>Experience with AI training, LLM evaluation, code QA, or rubric-based code review is a strong plus.</li></ul>"}