JavaScript Engineer
Up to $60/hr as listed
- Listed pay
- Up to $60/hr as listed
- Field
- Coding
- Languages
- English
- Where
17 countries
United States, Germany, Brazil, India, Bangladesh, Bhutan, Indonesia, Cambodia, Sri Lanka, Malaysia, Nepal, Philippines, Pakistan, Singapore, Thailand, Timor Leste, Vietnam- Type
- Contract, remote
- Posted on SME Careers
- First seen here
- 9 October 2026
Summary
As an hourly paid, fully remote JavaScript Engineer for AI Data Training, you will review complex AI-generated code and explanations or generate new ones, evaluate the reasoning quality and...
From the SME Careers listing
As an hourly paid, fully remote JavaScript Engineer for AI Data Training, you will review complex AI-generated code and explanations or generate new ones, evaluate the reasoning quality and step-by-step problem-solving, and provide expert feedback that helps models produce answers that are accurate, logical, and clearly explained. You will assess solutions for accuracy, clarity, and adherence to the prompt, identify errors in methodology or conceptual understanding, fact-check information, write high-quality explanations and model solutions that demonstrate correct methods, and rate and compare multiple AI responses based on correctness and reasoning quality. This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate that provides AI training data for many of the world’s largest AI companies and foundation model labs. Your work will directly help improve the world’s premier AI models while giving you the flexibility of impactful, detail-oriented remote contract work.
Important:
There is no immediate project for this role; however, if qualified, you will be among the first experts we reach out to when relevant opportunities arise. This will also provide you with access to future projects available through our expert network.
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.
Requirements
- 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.
Text above is the platform's own listing, shown as published. Check the details on SME Careers before applying.
Prepare for the assessment
Practice questions and what each platform says about its screening for this kind of role:
Terms in this listing
- Prompt
- The input given to a model: a question, an instruction or a conversation so far.
- Relevance
- How well a result or answer matches what the user was looking for.
- Edge case
- An unusual item the guidelines do not clearly cover. Projects usually ask you to flag it rather than guess.
- Annotation
- Adding labels or notes to data such as text, images, audio or video so a model can learn from it.
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