Senior Python Code Reviewer (DOCKER PROFICIENCY REQUIRED)

About OpenTrain

OpenTrain aggregates data-labeling and AI-training jobs from many companies and platforms into a single job board so qualified contributors can find work without hunting dozens of sites. Creating an OpenTrain account is free and applying takes only a few minutes.

We connect experienced reviewers with short-term and ongoing projects that shape how AI models behave by ensuring training data is accurate, secure, and useful.

About AI Training Work (Why this matters)

AI models learn from examples prepared and reviewed by people. Code review and annotation tasks like this one ensure model outputs are correct, safe, and aligned with developer intent.

This work is typically remote and flexible: many projects let you choose hours and workload, and contributors directly influence the quality of state-of-the-art systems.

• Work is fully remote and flexible; this posting expects under 20 hours per week.
• Tasks are part of the human feedback and data-labeling process that trains and refines AI systems.

The Role

We’re hiring Senior Python Code Reviewers to audit annotator evaluations of AI-generated Python code. You will run proof-of-work checks to confirm each snippet follows its prompt, executes correctly in an isolated environment, and meets security best practices.

Your reviews will catch rating errors, provide concise corrective feedback, and enforce project guideline standards to protect the accuracy and safety of training data.

• Position type: Contractor, Part-time.
• Time requirement: Less than 20 hours per week (remote, worldwide).
• Pay: $18 USD per hour (PAY_PER_HOUR).

What You’ll Do

Perform practical, hands-on validation of AI-generated Python snippets by executing code in isolated environments and comparing results to prompts and expected behaviors.

Provide short, constructive feedback and documentation inside the project’s QA workflow so annotators and project leads can act on mistakes quickly.

• Execute and validate code examples inside Docker containers for proof-of-work checks.
• Confirm code follows the prompt, handles edge cases, and passes relevant tests.
• Assess security concerns: injection, deserialization, race conditions, permissions issues.
• Use checklists, rubrics, and ticketing tools to record findings and assign scores.
• Flag rating errors and inconsistencies; write concise remediation instructions.

Requirements (Must Have)

Candidates must meet all of the following core requirements. We will verify these skills during the hiring process.

• Minimum seven years hands-on Python experience demonstrating advanced syntax and idioms.
• Deep Python mastery up to and including Python 3.12: stdlib, virtualenvs, dependency management.
• Advanced debugging and testing experience: pytest or unittest, coverage, profiling, and edge-case test design.
• Mandatory Docker proficiency for building, running, exec-ing into containers, multi-stage images, volume mounts, and troubleshooting.
• Secure-coding mindset: ability to identify injection, deserialization, race conditions, and permission errors.
• Proof-of-work code validation experience: sandboxed or container execution to verify functionality.
• Experience working within structured QA/annotation workflows: checklists, rubrics, and ticketing tools.
• Strong written English for concise, constructive feedback (CEFR B2+).
• Reliable remote work setup and the discipline to hit milestones and deadlines.

Preferred (Nice to Have)

The following are not required but will strengthen your application.

• Prior experience evaluating LLM or RLHF outputs.
• Familiarity with annotation platforms and labeling workflows.
• Mentoring or senior review experience on engineering teams.

Interview & Evaluation Process

Applicants will be evaluated by a structured interviewer called "Atlas-AI Interviewer" that probes the competencies listed above. The interviewer is designed to assess technical depth and written communication in a timed, professional format.

During the interview you should expect focused questions about Python (≤ 3.12), testing, secure coding, Docker usage, proof-of-work validation, and QA workflows. Answers will be recorded verbatim for the hiring panel.

• Interviewer conduct: neutral and professional; the process will not include coaching.
• Be prepared for follow-up drilling when answers are vague; the interviewer keeps conversation on schedule.
• Responses will be captured for review by the hiring team.

Logistics & Data Details

This role is contract, part-time, and remote; candidates may work from anywhere. Labeling work focuses on COMPUTER_CODE_PROGRAMMING data and COMPUTER_PROGRAMMING_CODING label types and uses OTHER labeling software as designated by the project.

Compensation is paid hourly at $18 USD. The role explicitly requires Docker proficiency and at least seven years of Python experience.

• Employment types: CONTRACTOR, PART_TIME.
• Data type: COMPUTER_CODE_PROGRAMMING; Label types: COMPUTER_PROGRAMMING_CODING.
• Labeling software: OTHER.

How to Apply

Create a free OpenTrain account and submit your application through this job posting. Applications typically take only a few minutes to complete.

Include a concise summary of your Python and Docker experience, examples of testing/debugging work, and any relevant RLHF or annotation platform experience if available.

• Be prepared to demonstrate Python and Docker skills during the interview.
• Make sure your written English demonstrates the concise, constructive style required for review feedback.