Senior Python Code Reviewer; Docker Proficiency

About Open Train

Open Train is the #1 platform for finding and building careers in AI training and data labeling. We help people start and grow careers teaching AI by connecting contributors with real projects, letting you build a profile, apply quickly, and work on the human side of how modern AI systems get trained.

AI training (also called data labeling or human feedback work) is the human layer behind modern models: people annotate, evaluate, and validate examples that shape model behavior. Work in this industry is highly flexible, often remote and part-time, and ranges from simple labels to specialist technical review for code, medical, or legal content.

You will audit annotator evaluations of AI-generated Python code and perform proof-of-work validation in isolated environments. Your reviews ensure each code snippet follows the prompt, executes correctly, and meets security best practices while preserving label quality and project guidelines.

• Run containerized checks to reproduce and validate code outputs and behavior.
• Verify that code matches prompts, handles edge cases, and includes adequate tests where applicable.
• Identify security issues (injection, unsafe deserialization, race conditions, permission errors) and report them clearly.
• Catch and correct rating errors from annotators, using project checklists and rubrics.
• Provide concise, constructive written feedback and documentation for annotators and project leads.

As a part-time contractor (under 20 hours/week) you’ll pick up review batches, spin up isolated environments (Docker), run proofs-of-work, score each item against a rubric, and file clear QA notes or tickets for problematic items. You will work within a structured QA workflow and communicate findings in written form.

• Receive a batch and checklist from the annotation platform.
• Build/run containers to execute or sandbox code snippets and tests.
• Record execution results, pass/fail outcomes, and security concerns.
• Submit rubric scores, short feedback comments, and any follow-up tickets.

All of the following are required and will be verified during screening.

• Minimum seven years of hands-on Python experience (compatible with Python