Node.js Code Review Specialist

About OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. We help freelancers discover projects, build a unified portfolio of AI training work, and grow durable careers contributing the human expertise that modern AI systems learn from.

As the hiring organization for this role, OpenTrain organizes the work, payments, and project details so you can focus on doing high-quality technical reviews and building proof of work on your OpenTrain profile.

About AI training and why it matters

AI training (also called data labeling or human feedback) is the human work that teaches models how to write, reason, and solve real problems. Reviewers and annotators supply the curated examples, evaluations, and expert judgments that determine how models behave.

This work is highly flexible, remote-friendly, and accessible to people with technical expertise—it's a chance to shape how state-of-the-art systems perform while building a visible portfolio of applied skills.

The role

As a Node.js Code Review Specialist you will review Node.js, JavaScript, and TypeScript code samples and backend engineering scenarios to produce detailed, high-quality annotations, evaluations, and written guidance that train and evaluate AI models.

This is contract, part-time work (estimated ~20 hours per week for 1–3 months). Work is remote and worldwide; communication and deliverables are in English. Hourly pay ranges $30–$90.

What you'll do

You will analyze code examples and backend patterns, surface correctness and performance issues, and document edge cases and trade-offs in plain language suitable for model training and mixed technical audiences.

• Review code samples for accuracy, efficiency, security, and best practices.
• Evaluate real-world Node.js scenarios and distributed backend engineering patterns.
• Document nuanced technical considerations, failure modes, and alternative solutions.
• Write clear, actionable feedback geared to training data and evaluation metrics.
• Collaborate asynchronously with project teams to refine guidance and examples.

Requirements

You must have demonstrated hands-on experience and an ability to explain technical decisions clearly in writing.

• Extensive hands-on experience with Node.js, JavaScript, and TypeScript.
• Strong debugging and problem-solving skills for distributed application systems.
• Deep understanding of backend architectures, common development patterns, and trade-offs.
• Clear written and verbal communication skills in English.
• Collaborative, detail-oriented approach to technical review and documentation.

Helpful background (not required)

These experiences make you especially effective in this role but are not strict prerequisites.

• Prior experience contributing to AI-related projects, model training, or evaluation initiatives.
• Experience working on large-scale, high-availability Node.js applications.
• Comfort with remote collaboration and asynchronous communication tools.

Who should apply

Apply if you enjoy reading and improving code, explaining trade-offs, and turning technical knowledge into structured feedback that trains AI. This role suits backend engineers, senior developers, and technical reviewers who want flexible, remote contract work and to build visible AI-training experience on OpenTrain.

Schedule, pay, and how it works

This contract role is remote and worldwide. Estimated time commitment is about 20 hours per week for a 1–3 month engagement. Hourly pay is $30–$90; actual rate within that range will be set per assignment.

You will complete review tasks, submit written evaluations, and collaborate asynchronously. OpenTrain handles contracting and payments so you receive timely compensation for completed work.

• Employment type: Contractor, Part-time.
• Languages: English required.
• Labeling work focuses on COMPUTER_CODE_PROGRAMMING with tasks like code evaluation and rating.

How to apply

Create or sign in to your OpenTrain profile, highlight your Node.js and backend review experience, and submit for this role. Include examples of code review or links to relevant work when available.

Successful candidates will be evaluated on technical experience, clarity of communication, and ability to produce structured, model-friendly feedback.