PHP (Laravel) Code Review & Evaluation

About OpenTrain

OpenTrain is the #1 platform for people starting and growing careers in AI training and data labeling. We connect contributors with projects that directly shape how state-of-the-art AI systems behave, offering flexible remote work and opportunities to build valuable skills in the fast-growing AI training industry.

• Work remotely for flexible, part-time projects that fit around studies or other jobs.
• Contribute to the human side of AI by evaluating and improving model outputs.

About AI Training Work

AI training (also called data labeling or human feedback work) is the practical process where people prepare, review, and improve the examples AI models learn from. For this role you will be evaluating generated code and explanations, a high-impact way to improve accuracy and developer-friendliness of coding assistants.

• Tasks include labeling, categorizing, and assessing AI-generated code snippets and explanations.
• Contributors often need domain expertise (here: Laravel) plus clear written communication to produce useful feedback.

The Role

We are hiring an experienced PHP developer with deep Laravel knowledge to evaluate AI-generated PHP/Laravel prompts, code, and explanations. You'll analyze correctness, efficiency, security, and adherence to Laravel best practices, and provide structured, actionable feedback that improves the quality of future model outputs.

• Part-time contractor role, less than 20 hours per week.
• Pay: $15 USD per hour (PAY_PER_HOUR).
• Remote and open worldwide; you will perform structured labeling and review tasks using the project's tooling (labeling software: OTHER).

What You'll Do

Your core task is to review AI-generated Laravel code and explanations and produce detailed labels and feedback. You will point out errors, inefficiencies, security issues, and suggest improvements aligned with Laravel best practices.

• Assess AI responses for correctness and adherence to Laravel conventions (MVC, Eloquent, Blade, middleware, etc.).
• Label and categorize code snippets and explanations for downstream model training.
• Suggest code fixes, performance optimizations, and security hardening steps.
• Explain issues and corrections in clear, structured English for both engineers and annotators.

Interview & Assessment Process

The selection process focuses on hands-on Laravel experience, debugging ability, and clear written communication. Expect technical questions, code-debug tasks, and sample evaluation assignments that mirror the actual review work.

• Experience assessment: describe real projects where you built full-stack Laravel features, APIs, authentication, and database integrations.
• Technical knowledge checks: identify and fix buggy code, explain security hardening, and discuss middleware, service providers, queues, and event handling.
• AI evaluation tasks: analyze AI-generated claims and implementations, identify inaccuracies, and provide structured corrections and rationale.
• Communication test: explain Laravel concepts simply and write concise feedback that a developer can act on.

Example Technical Check

You may be asked to spot issues in short code snippets and explain fixes. Example snippet you could be asked about:

use App\Models\User; $user = User::find(1); $user->update([ 'email' => 'newemail@example.com' ]);

• Explain what issue might occur (e.g., null result if user not found, mass-assignment, validation missing).
• Describe how to improve security when updating user data (validation, authorization, use of fillable/guarded, request objects).

Requirements

Candidates must meet the following requirements based on the project brief. We will verify hands-on experience during the interview.

• 5+ years hands-on experience with PHP and Laravel MVC architecture, Eloquent ORM, Blade templating, API development, and authentication systems.
• Proven experience with database optimization, performance tuning, and security best practices in Laravel apps.
• Strong English writing skills — role requires clear, structured feedback on AI outputs.
• Willingness to perform labeling and evaluative work: categorizing, annotating, and explaining corrections.
• Availability for less than 20 hours per week as a contractor (part-time).

Who Should Apply

Apply if you are a hands-on Laravel developer who enjoys debugging, teaching, and improving developer-facing documentation and code quality. This role suits people who can explain technical issues clearly in writing and who want flexible, remote, impactful work improving AI-assisted developer tools.

• Not a fit for candidates with only theoretical knowledge; practical, demonstrable Laravel experience is required.
• Prior experience evaluating AI-generated code is a plus but not strictly required if you can demonstrate strong Laravel expertise and communication skills.

Compensation & Logistics

This is a part-time contractor position paid hourly at $15 USD per hour. The project uses an external labeling platform (OTHER) and requires precise, structured feedback for model training. Work is remote and open worldwide.

• Employment type: Contractor, Part-time.
• Time requirement: Less than 20 hours/week.
• Label types: COMPUTER_PROGRAMMING_CODING; data type: COMPUTER_CODE_PROGRAMMING.

How to Apply

When applying, highlight specific Laravel projects and your role, describe a concrete performance or security improvement you implemented, and include examples of written technical feedback if available. Be prepared to complete a technical debugging task and a short AI-evaluation sample during the interview.

• Include years of Laravel experience and examples of production projects.
• Confirm availability (<20 hrs/week) and comfort with providing structured written feedback.
• Note: strong written English is required for labeling and review activities.