C Quality Assurance Lead - Remote

About the role

This role is a fast-growing AI Data Services company 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.

Responsibilities

• Quality monitoring: Spot-check C items, identify quality issues, provide feedback through DMs, and escalate recurring or critical issues.
• Code review: Evaluate AI-generated C code, debugging responses, pointer/memory examples, algorithmic solutions, tests, and technical explanations.
• Trainer/QA communication: Update contributors on Discord about guideline changes, workflow updates, and C-specific review standards.
• Question handling: Respond to questions around pointers, memory allocation, compilation, UB, portability, embedded constraints, testing, and rubric interpretation.
• Activation management: DM inactive contributors, track follow-ups, and flag availability issues.
• Documentation: Create and maintain C style guides, trackers, FAQs, examples, honeypots, calibration tasks, and onboarding materials.
• Onboarding: Run onboarding/training calls for C contributors.
• Risk review: Flag unsafe, non-compilable, misleading, memory-unsafe, or non-production-ready C recommendations.
• Process improvement: Identify recurring quality gaps and improve QA workflows.

Requirements

Strong grasp of English to follow guidelines and provide clear technical feedback.

3+ years of professional experience in C programming, systems programming, embedded development, firmware, operating systems, performance engineering, code review, QA, or technical mentoring.

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.

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.

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.

Experience leading or supporting remote teams of trainers, reviewers, engineers, coding mentors, or QAs is strongly preferred.

Highly organized and able to maintain style guides, trackers, FAQs, onboarding materials, honeypots, calibration tasks, and quality documentation.

Experience with AI training, LLM evaluation, code QA, or rubric-based code review is a strong plus.