C++ Quality Assurance Lead

About OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. We help freelancers discover projects, build a lasting portfolio of AI training work, and grow their skills across many technical domains. Creating an OpenTrain account is free.

About AI training work

AI training (also called data labeling, annotation, or human feedback) is the human side of building intelligent systems: people prepare, review, and rate examples that modern models learn from. This role is on the cutting edge of how AI models learn to write and reason about code.

Many contributors choose this work for the remote flexibility, part-time hours, and the chance to shape how state-of-the-art systems behave. You’ll be directly improving model outputs and the training data used to teach them.

The role

OpenTrain is recruiting a C++ Quality Assurance Lead to review AI-generated C++ code and trainer QA outputs, evaluate them against project rubrics, and deliver clear written feedback that raises quality and consistency. This is an hourly remote contractor role; OpenTrain is the hiring organization.

• Position type: Contractor, part-time.
• Expected workload: ~20+ hours per week.
• Estimated duration: 1 to 3 months.
• Location: United States only; English required.
• Pay: $75 USD per hour.

What you'll do

You will assess correctness, safety, performance, maintainability, and rubric adherence across C++ training projects. Your feedback will help trainers, improve labeling quality, and inform scalable QA processes.

• Review AI-generated C++ code, debugging responses, algorithmic solutions, tests, explanations, and performance recommendations.
• Spot-check items for correctness, memory safety, undefined behavior, race conditions, and inefficient algorithms.
• Verify compile-time validity and expected runtime behavior across common toolchains.
• Provide precise, constructive written feedback to contributors and escalate recurring or critical issues.
• Help build scalable QA processes, calibration tasks, onboarding materials, and documentation that improve consistency.

Requirements

Candidates must demonstrate strong professional experience with modern C++ and be comfortable producing clear technical feedback to remote contributors.

• Strong professional C++ experience in development, systems programming, performance engineering, embedded software, backend engineering, code review, QA, or technical mentoring.
• Deep knowledge of modern C++: RAII, smart pointers, templates, STL containers/algorithms, move semantics, concurrency, exceptions, and memory management.
• Ability to identify undefined behavior, memory leaks, dangling references, race conditions, non-compilable code, hallucinated APIs, and incomplete explanations.
• Clear English communication for written technical feedback and cross-team coordination.
• Experience reviewing AI-generated code, rubric-based evaluation, or LLM evaluation is a strong plus.

Helpful background and tools

Experience with common C++ toolchains and QA tooling will help you be effective from day one. You don’t need all items listed, but familiarity with these tools is valuable.

• Tooling: CMake, GCC, Clang, MSVC, GDB, LLDB, sanitizers, Valgrind.
• Testing & libraries: GoogleTest, Catch2, Boost.
• Process: GitHub, CI/CD, profiling tools, static analyzers.
• Experience leading or mentoring trainers, reviewers, engineers, or QA teams and maintaining style guides, FAQs, and calibration tasks.

How the engagement works

This is a remote, hourly contractor engagement managed by OpenTrain. Expected commitment is about 20+ hours per week for 1–3 months at a fixed rate of $75/hr. Work is US-based and conducted in English.

Apply by creating or using your OpenTrain account — profiles help you show experience and manage work across projects. Your work will include rubric-driven evaluations and RLHF/evaluation rating tasks for C++ training data.