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JavaScript Developer

AgileGrid Solutions

full-remotemidcontractother United States Today via LinkedIn

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Tags

JavaScriptProgrammingCode ReviewData AnnotationTechnical WritingPythonJavaC++Bilingual Communication (English/Spanish)LLM Training

About the role

Role Overview

You will work as an AI Data Annotator / Programming Expert, helping train AI models to solve complex programming challenges. The work is remote and centers on creating programming questions, reviewing AI-generated code, and providing high-quality feedback.

Responsibilities

  • Create and answer computer science/programming-related questions to support AI training.
  • Review and analyze AI-generated code for correctness, efficiency, and best-practice adherence.
  • Analyze and rank AI responses based on accuracy and relevance.
  • Provide clear, detailed, and constructive feedback to improve model responses.
  • Collaborate to refine data annotation processes and improve model training quality.
  • Maintain professionalism and consistency in all tasks.

Requirements

  • Bachelor’s degree or higher in Computer Science or a related field.
  • Proficiency in one or more programming languages, including Python, Java, JavaScript, or C++.
  • Ability to fluently explain complex programming concepts in English and Spanish.
  • Strong command of grammar, punctuation, and technical writing standards in both languages.

Preferred Qualifications

  • At least 1 year of experience as a Software Engineer, Back End Developer, or Full Stack Developer.

Benefits

  • Flexible remote work (work from anywhere in the remote-first model).
  • Opportunity to contribute to innovative AI projects.
  • Competitive compensation.
  • Access to a global community of AI contributors.
  • Ongoing learning opportunities through exposure to cutting-edge AI work.
  • Supportive culture focused on reliability and flexibility.

About AgileGrid Solutions

Outlier AI, owned and operated by Scale AI, advances artificial intelligence through high-quality data annotation and human feedback. The company focuses on building a reliable, transparent, and flexible platform that supports contributors worldwide to help train and improve large language models (LLMs).

Scraped 5/16/2026

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