PHP (Laravel) Code Reviewer For AI Evaluation

About OpenTrain

OpenTrain is the #1 platform for people building careers in AI training and data labeling. We hire contractors to evaluate model outputs, label data, and help shape the behavior of modern AI systems.

As the hiring and contracting organization for this role, OpenTrain connects skilled developers with flexible, remote AI evaluation projects that pay by the hour and let you work under 20 hours per week.

Why AI Training Work Matters

AI training (data labeling and human feedback) is how real people teach models to produce correct, safe, and useful results. Contributors review code, rank responses, and correct mistakes so models learn reliable patterns.

These projects are 100% remote, often flexible in schedule, and let experienced developers shape how AI systems handle developer-focused tasks like code generation and technical explanations.

The Role

You will evaluate AI-generated PHP (Laravel) prompts, code snippets, and explanations: label correctness, identify bugs or inefficiencies, and write structured, actionable feedback that helps both models and developer users.

This role also requires conducting AI-driven technical interviews with applicants: verifying hands-on Laravel experience, testing debugging and optimization skills, and judging candidates’ ability to communicate technical concepts clearly.

• Rate: USD 15 per hour (PAY_PER_HOUR).
• Time: Less than 20 hours per week, part-time contractor work.
• Location: Remote — worldwide applicants welcome.
• Employment types: Contractor, Part-time.

What You’ll Do

Perform careful, structured reviews of AI-generated PHP and Laravel content. Your assessments ensure outputs follow Laravel best practices, are secure, and are performant.

Run short technical interviews and hands-on debugging exercises with candidates, following the provided evaluation guidelines. Record labels, categorizations, and written feedback consistently.

• Analyze AI-generated prompts, code, and explanations for correctness and clarity.
• Label and categorize code snippets (e.g., correct, incorrect, security risk, inefficient).
• Identify bugs, performance issues, and security vulnerabilities; suggest fixes and improvements.
• Conduct interview questions and debugging exercises to validate candidates’ real-world Laravel experience.
• Write concise, structured feedback in clear English suitable for training data and human review.

Requirements

This role preserves every technical requirement from the project brief: applicants must have demonstrable Laravel expertise and strong written English.

We will verify experience and hands-on ability during interviews and sample tasks; candidates without practical, real-world Laravel work will be declined.

• 5+ years hands-on PHP (Laravel) development experience, working with Laravel’s MVC architecture.
• Strong experience with Eloquent ORM, Blade templating, API development, and authentication systems.
• Experience with database optimization, performance tuning, and security best practices in Laravel.
• Excellent written English for producing structured, precise feedback.
• Reliable internet access and ability to work under 20 hours per week as a contractor.

Interview & Evaluation Guidelines

You will follow a structured evaluation script that tests real-world Laravel skills, debugging ability, and clarity of explanation. The process probes depth and requests concrete examples when answers are vague.

Example tasks and checks provided in the project brief are part of the interview flow and must be used to assess candidates consistently.

• Experience assessment: ask candidates to describe real projects (authentication, APIs, DB integration) and probe for concrete challenges they solved.
• Technical check: present a buggy Laravel snippet, ask for diagnosis, fixes, and security improvements (e.g., validation, mass assignment, authorization).
• AI evaluation: assess incorrect AI claims (example: "Eloquent does not support relationships") and require a clear correction and explanation.
• Communication check: ask candidates to explain dependency injection or when to use queues in simple terms.
• Final confirmation: verify prior experience evaluating AI-generated code, availability, and readiness for structured labeling tasks.

How Selection Works

Applicants are evaluated by completing a short sample review and participating in a technical interview that follows the provided guidelines. Successful testers are invited to contract part-time labeling and evaluation work.

All hiring and contracting is managed by OpenTrain. The hiring process focuses on demonstrated, hands-on Laravel experience and the ability to produce concise, high-quality written feedback.

• Prepare examples of past Laravel projects and be ready to walk through specific optimizations or security fixes you made.
• Expect a short practical code review task and one or more interview questions testing debugging and evaluation skills.
• If you meet the technical bar and communication expectations, you will be offered contractor work at the listed hourly rate.