About the role

Role Overview

JavaScript Developer (AI Training) to evaluate and improve AI-generated JavaScript code for correctness, efficiency, and alignment with modern engineering standards. This is a fully remote, flexible hourly contract (10–40 hours/week). No prior AI background is required.

What You’ll Do

Review and evaluate AI-generated JavaScript code for:
- Correctness
- Efficiency
- Compliance with modern ES6+ standards
Write high-quality JavaScript solutions across varied difficulty levels
Produce clear, human-readable explanations of code logic and problem-solving approach
Identify edge cases, bugs, and failure points in AI-generated web and backend code
Provide structured, actionable feedback to improve how AI models reason about and write code
Work independently and asynchronously, on your own schedule

Who You Are

Deep familiarity with core JavaScript concepts, including:
- async/await
- Closures
- Prototypal inheritance
- DOM manipulation
3–5+ years hands-on experience using modern JavaScript frameworks such as React, Node.js, or Vue
Ability to write clean, well-reasoned code and explain your thinking in writing
Strong attention to detail and systematic debugging/issue-spotting
Self-motivated and reliable while working without supervision
Bachelor’s degree or higher in Computer Science or a related technical field (preferred)

Nice to Have

Experience with data labeling, RLHF, or other AI training/evaluation projects
Familiarity with TypeScript or adjacent JavaScript technologies
Background in code review, technical writing, or software quality assurance
Exposure to backend JavaScript environments and RESTful API development

Why Join Us

Work on cutting-edge AI projects with leading research labs
Fully remote and flexible; meaningful, task-based freelance autonomy
Potential for ongoing work and contract extension as new projects launch

About Alignerr

Alignerr is an organization focused on AI training and evaluation, helping improve how AI models write and understand code. The role sits at the intersection of software engineering quality and AI code assessment, with work that supports modern AI development alongside research labs.

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