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Full-Stack Developer - AI Trainer (Uruguay)

Job Overview

Location

Uruguay

Job Type

Part-time

Category

Software Engineering

Date Posted

June 13, 2026

Full Job Description

đź“‹ Description

  • • Design and implement multi-file coding tasks focused on bug resolution, feature implementation, refactoring, and migration in production-like environments.
  • • Write clear, precise natural-language specifications that define coding challenges and expected outcomes for AI training purposes.
  • • Develop and extend comprehensive unit and integration test suites using frameworks such as pytest, Jest, JUnit, xUnit, or Go testing to validate code correctness.
  • • Create realistic software engineering scenarios that mirror real-world development workflows and challenges faced by professional engineers.
  • • Review peer-generated coding tasks for correctness, clarity, realism, and alignment between specifications and implementation.
  • • Identify edge cases, ambiguities, logical inconsistencies, and potential failure modes in both task designs and submitted solutions.
  • • Ensure strict alignment between task specifications, reference implementations, and expected outputs to maintain high-quality training data for AI models.
  • • Work within large, complex codebases to debug issues, refactor legacy components, and execute production-grade migrations.
  • • Contribute to the evaluation of software engineering tasks by providing structured, actionable feedback on code quality, architecture, and test coverage.
  • • Operate as a project-based consultant with full autonomy over schedule and workload, delivering completed tasks on a per-project basis.
  • • Use professional-grade development tools of your choice to complete assignments; no company-provided hardware or software is provided.
  • • Maintain advanced written proficiency in English to produce technically accurate and linguistically clear documentation, specifications, and feedback.
  • • Collaborate asynchronously with a global team of experts to refine AI training datasets through iterative task design and peer review.
  • • Simultaneously engage with other vendors or employers, provided such arrangements do not conflict with the terms of this engagement.
  • • Deliver high-quality, production-realistic coding tasks that are used to train and evaluate large language models in software engineering contexts.
  • • Generate complete reference implementations that serve as gold-standard examples for AI model training and assessment.
  • • Produce robust validation artifacts including test suites, documentation, and review annotations that ensure task reliability and reproducibility.

🎯 Requirements

  • • Advanced professional written proficiency in English
  • • 3–7 years of professional software engineering experience
  • • Strong proficiency in Python and JavaScript/TypeScript
  • • Backend or full-stack development experience in production systems
  • • Experience with testing frameworks (e.g., pytest, Jest, JUnit, xUnit, Go testing)
  • • Proven ability to debug and navigate large, multi-file codebases

🏖️ Benefits

  • • Project-based compensation paid per completed task
  • • Full control over schedule and workload
  • • Ability to work remotely with no geographic restrictions
  • • Opportunity to work alongside leading AI labs on cutting-edge training data
  • • Flexibility to accept concurrent engagements with other vendors or employers
  • • No requirement for company-provided tools or equipment

Skills & Technologies

Python
JavaScript
TypeScript
Java
Go
Full Stack
Remote

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About Anyone AI Inc.

Anyone AI provides no-code computer-vision infrastructure that lets companies build, train and deploy image and video models without machine-learning teams. Its cloud platform automates data labeling, model optimization and edge deployment for retail, manufacturing, logistics and healthcare use cases. The company offers pre-trained APIs for object detection, counting and anomaly identification, plus dashboards for continuous monitoring and compliance. Founded in 2021, it targets enterprises seeking rapid AI adoption while avoiding costly specialists and infrastructure setup.

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