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Javascript Developer

Remote Smith

3.9
3 reviews
Remote Smith
Job Type   /   Job Level
Contract   /   Senior Executive
Job Location
APAC
Salary Range
USD 3,500 - USD 7,000 (Monthly)
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Your profile

  • Minimum 2+ years of professional JavaScript experience in production environments.
  • Strong understanding of closures, async/await, prototype-based inheritance, and JavaScript event loop behavior, with deep proficiency in modern Vanilla JavaScript (ES6/ES2015+).
  • Proven ability to evaluate correctness, readability, and performance of JavaScript code, including identifying subtle logic and edge-case issues.
  • Hands-on work experience in software engineering, preferably in roles involving code review, mentoring, or technical design discussions.
  • Significant experience using LLMs or AI coding assistants while programming, combined with a critical mindset for validating their output.
  • Excellent English writing skills, capable of producing clear, concise, and pedagogical technical explanations.
  • Strong proficiency with at least one major frontend framework (such as React, Angular, or Vue.js) or backend runtime (such as Node.js with Express or NestJS).
  • Minimum Bachelor’s degree in Computer Science or a closely related technical field.
  • Previous experience with AI data training, data annotation, or evaluation of AI-generated technical content is a strong plus; Minimum C1 English proficiency and a highly detail-oriented working style are required.
  • Preferred: contributions or merged PRs in JavaScript or TypeScript open-source projects, familiarity with bundlers and tooling (Webpack, Vite, Rollup), frontend–backend integration and Node.js runtime behavior, reviewing typed API layers, DTOs, or schema-driven designs, and experience evaluating frontend logic, async patterns, and state management.


Key responsibilities

  • Develop AI Training Content: Create detailed prompts in various topics and responses to guide AI learning, ensuring the models reflect a comprehensive understanding of diverse subjects.
  • Optimize AI Performance: Evaluate and rank AI responses to enhance the model's accuracy, fluency, and contextual relevance.
  • Ensure Model Integrity: Test AI models for potential inaccuracies or biases, validating their reliability across use cases.


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