The work
You will lead quality checks for Python work used in AI training projects. This includes reviewing AI-generated code, debugging responses, backend snippets, automation scripts, tests, explanations, and work completed by trainers and reviewers.
You will judge whether code is correct, executable, clear, maintainable, secure, efficient, and aligned with project rubrics. You will also help other contributors understand Python quality standards and improve review workflows.
- Review Python code and explanations against project guidelines and rubrics.
- Check logic, runtime behavior, debugging, readability, performance, security, test coverage, formatting, and instruction-following.
- Spot-check submissions, document quality problems, give precise written feedback, and escalate recurring or critical issues.
- Answer questions about Python syntax, testing, packages, typing, security, and performance.
- Create and maintain style guides, FAQs, examples, trackers, onboarding materials, and other documentation.
- Support contributor onboarding and training while identifying recurring quality gaps.
What it pays and takes
This is a remote, part-time contractor role open to candidates in the United States. The role is listed as entry level, and the work requires strong Python knowledge plus professional experience in software development, QA, code review, teaching, or technical mentoring.
- Pay: $70 per hour.
- Time: 20+ hours per week.
- Location: Remote and open to candidates in the United States.
- Language: Strong written English.
- Experience level: Entry level.
- Education: A bachelor's or master's degree in computer science, software engineering, data science, information technology, or equivalent professional software engineering experience.
- Experience: At least three years in Python development, backend engineering, automation, scripting, data workflows, code review, QA, teaching, or technical mentoring.
- Python skills: Data structures, functions, classes, modules, exceptions, iterators, generators, packaging, and testing.
- Quality judgment: Ability to find incorrect logic, non-executable code, unsafe operations, inefficient algorithms, fabricated APIs, and incomplete explanations.
- Helpful experience: pytest, unittest, typing, mypy, pip, poetry, virtual environments, Python web frameworks, GitHub, Docker, or CI/CD.
- Helpful background: Supporting remote trainer, reviewer, engineering, or QA teams, plus experience with AI training, data annotation, LLM evaluation, or rubric-based code review.
How it works
Apply on OpenTrain with your resume, then complete the application on the hiring site.
About AI training work
AI training is the human work behind systems that learn from examples. People review code and other model outputs, rate quality, and give clear feedback so AI systems become more useful and reliable; experienced contributors are often needed for specialized technical work.